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Powered by Question2AnswerWhat does the term "value creation" within the Human Resources (HR) context refer to?
https://mathsgee.com/qna/17061/what-does-the-term-value-creation-within-the-human-resources-hr-context-refer-to
<p>Value Creation
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The term value creation within the Human Resources (HR) context refers to improving the employees productivity and functionality. The current HR environment is highly competitive. Consequently, it has become a core responsibility of the HR managers to give their employees an opportunity to demonstrate their value or contribution towards the organizations success during the tough moments. Both the unionized and union-free private sector workplaces must create value for their workers and understand the factors that will affect workplace relations in the future.
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The private sector businesses believe in increasing the competitive strength of their brands. These workplaces can be characterized by value orientation. They use different approaches to creating value for the internal and external stakeholders. They also concentrate on improving the workplace relations because they see harmony as an indispensable component of their success. These methods are essential for the private sector because they can improve the workplace relations. Firstly, the private sector organizations should encourage honesty (truth) at the workplace. The current workplace environment is facing the scarcity of truth. Consumers attach a lot of value to honesty due to its growing shortage. Therefore, truth is a fundamental component that the organizations must encourage among the employees. It promotes harmony at the workplace and develops trust among the consumers. Secondly, the private sector companies should advise their employees to practice personality power. Speaking to clients genuinely and enthusiastically is an example of a virtue that improves the relationship between an employee and a customer.
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Furthermore, it is necessary for an organization to train its workforce in order to attract customers through creativity. They must think of the new ways of designing and packaging the products to make them appealing. We increase the value of things when we make them aesthetically appealing. Meeting the needs of the customers and employees on time is also a strategy that the private sector should consider when creating value. The HR department should start by reaching the employees expectations, e.g. by granting them a safe workplace. Then the HR managers should proceed to utilize market research data and train the workers about the customers needs that they must achieve through the products and services.
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Strategic planning is an invaluable tool that the HR managers must use to create and sustain value. The role of business management encompasses numerous challenges, especially during the turbulent moments. Thus, the leaders should provide their workers with the strategic plans that can increase their resilience. As part of these strategic plans, the management should provide the employees with educational and training opportunities. The plans of the unionized organizations should allow open dialogue with the unions, especially during the recessions. Such dialogues should aim to reduce incidences of strikes and slowdowns among the workers. Such issues undermine the value of the end-products that the consumers get. Another strategy is for the HR professionals to identify the available talents, more so for the positions that are difficult to fill. This strategy includes recruiting the highly experienced personnel who have lost their jobs in the competing firms. These elements of strategic planning ensure that the HR department maintains a highly skilled, competent, and experienced workforce that can meet the market demands effectively.
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Value creation allows the HR professionals to enhance a calm atmosphere by eliminating on-the-job stress. The HR managers keep their employees positive and creative through value creation. This element also empowers the employees by equipping them with the necessary competencies for performing their tasks. They can also use the alternative ways of executing their duties. The outcome is a knowledgeable and highly creative workforce that understands different solutions to problems. Therefore, it is compelling for both the union and non-union work environments to use their HR professionals in creating value for both the stakeholders and the customers. The value that the HR managers create determines the competitive strength of the organizations brands.
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The future of the workplace relations for the union and union-free workplaces depends on the extent to which the private sector organizations will implement value creation as a competitive strategy. However, the challenge of the private sector institutions is that they consider value creation as an overhead. Nonetheless, the HR department reserves the responsibility of continuing to provide a reasonable work environment; and value creation is a compelling factor that businesses must consider. The private sector corporations must begin viewing value creation as an asset and not a liability. Moreover, the firms that do not create value for the customers and employees will lose in the competitive struggle because they will not attract the competent talent. The buyers will also stop consuming their goods and services because they will feel that such businesses do not meet their needs. Consequently, value creation is the path that all businesses will have to follow.
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The second factor that will determine the future of workplace relations is knowledge management. Currently, the organizations are facing a situation whereby knowledge determines capabilities. The leading private organizations are the ones that operate as learning organisms that are capable of using knowledge to adapt to the highly competitive environment. The well-performing corporations consider knowledge as the asset for gaining competitiveness. Consequently, they are modifying their human resources using the knowledge, e.g. through training and development. They encourage their employees to remain flexible to change so that they will adapt to the new knowledge easily. The efficient management of the cognitive resources is a technique that organizations should utilize as a way of creating value internally and externally. The employees should apply the knowledge towards producing high-quality commodities that will compete well in the market.
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What is more, the ability to preserve and protect knowledge will be a critical factor as well. It is not enough for a business to discover knowledge. Protecting the knowledge from the competitors will be an even more important factor than knowledge discovery. The future private sector workplaces will perceive knowledge as an innovation that their competitors should not copy. Therefore, the organizations shall train their workers to protect their knowledge.
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Finally, the HR officials ought to focus on the short-term and long-term goals as part of value creation. Most HR professionals only focus on the short-term reactions while forgetting the long-term commitments. It will be vital for HR managers to change their cultural perspectives about the organizational goals. They should also consider the roles of the junior employees in achieving the short- and long-term goals and prepare them adequately to achieving them.
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In conclusion, value creation is a vital intervention that the private companies are capitalizing on in the modern world. Added value enables the corporations to increase their brands competitiveness. Encouraging honesty, practicing personality power, applying creativity, and meeting the needs of the buyers are some of the value addition strategies that the private sector businesses are using presently. In the future, the private sector corporations will change their perspective about value creation as an overhead. They will implement the strategies to create more value for their employees and customers. They will also focus on managing their knowledge more properly while protecting it from the competitors.</p>
<p><img alt="" src="https://mathsgee.com/qna/?qa=blob&qa_blobid=7320753302697028328" style="height:450px; width:600px"></p>Artificial Intelligencehttps://mathsgee.com/qna/17061/what-does-the-term-value-creation-within-the-human-resources-hr-context-refer-toWed, 05 Aug 2020 10:30:28 +0000Answered: How is True Positive Rate and Recall related? Write the equation.
https://mathsgee.com/qna/17031/how-is-true-positive-rate-and-recall-related-write-the-equation?show=17060#a17060
True Positive Rate = Recall. Yes, they are equal having the formula (TP/TP + FN).Data Sciencehttps://mathsgee.com/qna/17031/how-is-true-positive-rate-and-recall-related-write-the-equation?show=17060#a17060Wed, 05 Aug 2020 07:06:38 +0000Answered: You have built a multiple regression model. Your model R² isn’t as good as you wanted. For improvement, your remove the intercept term, your model R² becomes 0.8 from 0.3. Is it possible? How?
https://mathsgee.com/qna/17032/you-have-built-a-multiple-regression-model-your-model-r-isnt-as-good-as-you-wanted-for-improvement-your-remove-the-intercept-term-your-model-r-becomes-0-8-from-0-3-is-it-possible-how?show=17059#a17059
<p>Yes, it is possible. We need to understand the significance of intercept term in a regression model. The intercept term shows model prediction without any independent variable i.e. mean prediction. The formula of R² = 1 – ∑(y – y´)²/∑(y – ymean)² where y´ is predicted value. </p>
<p>When intercept term is present, R² value evaluates your model wrt. to the mean model. In absence of intercept term (<code>ymean</code>), the model can make no such evaluation, with large denominator, <code>∑(y - y´)²/∑(y)²</code> equation’s value becomes smaller than actual, resulting in higher R².</p>Data Sciencehttps://mathsgee.com/qna/17032/you-have-built-a-multiple-regression-model-your-model-r-isnt-as-good-as-you-wanted-for-improvement-your-remove-the-intercept-term-your-model-r-becomes-0-8-from-0-3-is-it-possible-how?show=17059#a17059Wed, 05 Aug 2020 07:05:56 +0000Answered: How would you check if he’s true? Without losing any information, can you still build a better model?
https://mathsgee.com/qna/17033/how-would-you-check-if-hes-true-without-losing-any-information-can-you-still-build-a-better-model?show=17058#a17058
To check multicollinearity, we can create a correlation matrix to identify & remove variables having correlation above 75% (deciding a threshold is subjective). In addition, we can use calculate VIF (variance inflation factor) to check the presence of multicollinearity. VIF value <= 4 suggests no multicollinearity whereas a value of >= 10 implies serious multicollinearity. Also, we can use tolerance as an indicator of multicollinearity.<br />
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But, removing correlated variables might lead to loss of information. In order to retain those variables, we can use penalized regression models like ridge or lasso regression. Also, we can add some random noise in correlated variable so that the variables become different from each other. But, adding noise might affect the prediction accuracy, hence this approach should be carefully used.Data Sciencehttps://mathsgee.com/qna/17033/how-would-you-check-if-hes-true-without-losing-any-information-can-you-still-build-a-better-model?show=17058#a17058Wed, 05 Aug 2020 07:01:05 +0000Answered: When is Ridge regression favorable over Lasso regression?
https://mathsgee.com/qna/17034/when-is-ridge-regression-favorable-over-lasso-regression?show=17057#a17057
Lasso regression (L1) does both variable selection and parameter shrinkage, whereas Ridge regression only does parameter shrinkage and end up including all the coefficients in the model. In presence of correlated variables, ridge regression might be the preferred choice. Also, ridge regression works best in situations where the least square estimates have higher variance. Therefore, it depends on our model objective.Data Sciencehttps://mathsgee.com/qna/17034/when-is-ridge-regression-favorable-over-lasso-regression?show=17057#a17057Wed, 05 Aug 2020 06:59:16 +0000Answered: Rise in global average temperature led to decrease in number of pirates around the world. Does that mean that decrease in number of pirates caused the climate change?
https://mathsgee.com/qna/17035/rise-in-global-average-temperature-led-to-decrease-in-number-of-pirates-around-the-world-does-that-mean-that-decrease-in-number-of-pirates-caused-the-climate-change?show=17056#a17056
After reading this question, you should have understood that this is a classic case of “causation and correlation”. No, we can’t conclude that decrease in number of pirates caused the climate change because there might be other factors (lurking or confounding variables) influencing this phenomenon.<br />
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Therefore, there might be a correlation between global average temperature and number of pirates, but based on this information we can’t say that pirated died because of rise in global average temperature.Data Sciencehttps://mathsgee.com/qna/17035/rise-in-global-average-temperature-led-to-decrease-in-number-of-pirates-around-the-world-does-that-mean-that-decrease-in-number-of-pirates-caused-the-climate-change?show=17056#a17056Wed, 05 Aug 2020 06:58:28 +0000Answered: While working on a data set, how do you select important variables? Explain your methods.
https://mathsgee.com/qna/17036/while-working-on-a-data-set-how-do-you-select-important-variables-explain-your-methods?show=17055#a17055
<p>Following are the methods of variable selection you can use:</p>
<ol>
<li>Remove the correlated variables prior to selecting important variables</li>
<li>Use linear regression and select variables based on p values</li>
<li>Use Forward Selection, Backward Selection, Stepwise Selection</li>
<li>Use Random Forest, Xgboost and plot variable importance chart</li>
<li>Use Lasso Regression</li>
<li>Measure information gain for the available set of features and select top n features accordingly.</li>
</ol>Data Sciencehttps://mathsgee.com/qna/17036/while-working-on-a-data-set-how-do-you-select-important-variables-explain-your-methods?show=17055#a17055Wed, 05 Aug 2020 06:57:55 +0000Answered: What is the difference between covariance and correlation?
https://mathsgee.com/qna/17037/what-is-the-difference-between-covariance-and-correlation?show=17054#a17054
Correlation is the standardized form of covariance.<br />
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Covariances are difficult to compare. For example: if we calculate the covariances of salary ($) and age (years), we’ll get different covariances which can’t be compared because of having unequal scales. To combat such situation, we calculate correlation to get a value between -1 and 1, irrespective of their respective scale.Data Sciencehttps://mathsgee.com/qna/17037/what-is-the-difference-between-covariance-and-correlation?show=17054#a17054Wed, 05 Aug 2020 06:57:12 +0000Answered: Is it possible capture the correlation between continuous and categorical variable? If yes, how?
https://mathsgee.com/qna/17038/is-it-possible-capture-the-correlation-between-continuous-and-categorical-variable-if-yes-how?show=17053#a17053
Yes, we can use ANCOVA (analysis of covariance) technique to capture association between continuous and categorical variables.Data Sciencehttps://mathsgee.com/qna/17038/is-it-possible-capture-the-correlation-between-continuous-and-categorical-variable-if-yes-how?show=17053#a17053Wed, 05 Aug 2020 06:56:32 +0000Answered: Both being tree based algorithm, how is random forest different from Gradient boosting algorithm (GBM)?
https://mathsgee.com/qna/17039/both-being-tree-based-algorithm-how-is-random-forest-different-from-gradient-boosting-algorithm-gbm?show=17052#a17052
The fundamental difference is, random forest uses bagging technique to make predictions. GBM uses boosting techniques to make predictions.<br />
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In bagging technique, a data set is divided into n samples using randomized sampling. Then, using a single learning algorithm a model is build on all samples. Later, the resultant predictions are combined using voting or averaging. Bagging is done is parallel. In boosting, after the first round of predictions, the algorithm weighs misclassified predictions higher, such that they can be corrected in the succeeding round. This sequential process of giving higher weights to misclassified predictions continue until a stopping criterion is reached.<br />
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Random forest improves model accuracy by reducing variance (mainly). The trees grown are uncorrelated to maximize the decrease in variance. On the other hand, GBM improves accuracy my reducing both bias and variance in a model.Data Sciencehttps://mathsgee.com/qna/17039/both-being-tree-based-algorithm-how-is-random-forest-different-from-gradient-boosting-algorithm-gbm?show=17052#a17052Wed, 05 Aug 2020 06:55:44 +0000Answered: How does the tree decide which variable to split at the root node and succeeding nodes?
https://mathsgee.com/qna/17040/how-does-the-tree-decide-which-variable-to-split-at-the-root-node-and-succeeding-nodes?show=17051#a17051
<p>A classification trees makes decision based on Gini Index and Node Entropy. In simple words, the tree algorithm find the best possible feature which can divide the data set into purest possible children nodes.</p>
<p>Gini index says, if we select two items from a population at random then they must be of same class and probability for this is 1 if population is pure. We can calculate Gini as following:</p>
<ol>
<li>Calculate Gini for sub-nodes, using formula sum of square of probability for success and failure (p^2+q^2).</li>
<li>Calculate Gini for split using weighted Gini score of each node of that split</li>
</ol>
<p>Entropy is the measure of impurity as given by (for binary class):</p>
<p>$$ \text{Entropy} = - p \log_{2}p - q\log_{2}q $$</p>
<p>Here p and q is probability of success and failure respectively in that node. Entropy is zero when a node is homogeneous. It is maximum when a both the classes are present in a node at 50% – 50%. Lower entropy is desirable.</p>Data Sciencehttps://mathsgee.com/qna/17040/how-does-the-tree-decide-which-variable-to-split-at-the-root-node-and-succeeding-nodes?show=17051#a17051Wed, 05 Aug 2020 06:53:25 +0000Answered: What is going on? Haven’t you trained your model perfectly?
https://mathsgee.com/qna/17041/what-is-going-on-havent-you-trained-your-model-perfectly?show=17050#a17050
The model has over-fitted. Training error 0.00 means the classifier has mimicked the training data patterns to an extent, that they are not available in the unseen data. Hence, when this classifier was run on unseen sample, it couldn’t find those patterns and returned prediction with higher error. In random forest, it happens when we use larger number of trees than necessary. Hence, to avoid these situation, we should tune number of trees using cross validation.Data Sciencehttps://mathsgee.com/qna/17041/what-is-going-on-havent-you-trained-your-model-perfectly?show=17050#a17050Wed, 05 Aug 2020 06:50:32 +0000Answered: Why is OLS as bad option to work with? Which techniques would be best to use? Why?
https://mathsgee.com/qna/17042/why-is-ols-as-bad-option-to-work-with-which-techniques-would-be-best-to-use-why?show=17049#a17049
In such high dimensional data sets, we can’t use classical regression techniques, since their assumptions tend to fail. When p > n, we can no longer calculate a unique least square coefficient estimate, the variances become infinite, so OLS cannot be used at all.<br />
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To combat this situation, we can use penalized regression methods like lasso, LARS, ridge which can shrink the coefficients to reduce variance. Precisely, ridge regression works best in situations where the least square estimates have higher variance.<br />
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Among other methods include subset regression, forward stepwise regression.Data Sciencehttps://mathsgee.com/qna/17042/why-is-ols-as-bad-option-to-work-with-which-techniques-would-be-best-to-use-why?show=17049#a17049Wed, 05 Aug 2020 06:49:15 +0000Answered: What is convex hull ?
https://mathsgee.com/qna/17043/what-is-convex-hull?show=17048#a17048
Convex hull represents the outer boundaries of the two group of data points given that the data is linearly separable. Once convex hull is created, we get maximum margin hyperplane (MMH) as a perpendicular bisector between two convex hulls. MMH is the line which attempts to create greatest separation between two groups.Data Sciencehttps://mathsgee.com/qna/17043/what-is-convex-hull?show=17048#a17048Wed, 05 Aug 2020 06:48:23 +0000Answered: We know that one hot encoding increasing the dimensionality of a data set. But, label encoding doesn’t. How ?
https://mathsgee.com/qna/17044/we-know-that-one-hot-encoding-increasing-the-dimensionality-of-a-data-set-but-label-encoding-doesnt-how?show=17047#a17047
<p>Using one hot encoding, the number of features in a data set increases because it creates a new variable for each level present in categorical variables. For example: let’s say we have a variable ‘color’. The variable has 3 levels namely Red, Blue and Green. One hot encoding ‘color’ variable will generate three new variables as <code>Color.Red</code>, <code>Color.Blue</code> and <code>Color.Green</code> containing 0 and 1 value.</p>
<p>In label encoding, the levels of a categorical variables gets encoded as 0 and 1, so no new variable is created. Label encoding is majorly used for binary variables.</p>Data Sciencehttps://mathsgee.com/qna/17044/we-know-that-one-hot-encoding-increasing-the-dimensionality-of-a-data-set-but-label-encoding-doesnt-how?show=17047#a17047Wed, 05 Aug 2020 06:46:53 +0000Answered: What cross validation technique would you use on time series data set? Is it k-fold or LOOCV?
https://mathsgee.com/qna/17045/what-cross-validation-technique-would-you-use-on-time-series-data-set-is-it-k-fold-or-loocv?show=17046#a17046
<p>I would use any of the two methods because a time series is sequential in a chronological manner.</p>
<p>In time series problems, k fold is not ideal because there might be some pattern in year 4 or 5 which is not in year 3. Resampling the data set will separate these trends, and we might end up validation on past years, which is incorrect. Instead, we can use forward chaining strategy with 5 fold as shown below:</p>
<ul>
<li>fold 1 : training [1], test [2]</li>
<li>fold 2 : training [1 2], test [3]</li>
<li>fold 3 : training [1 2 3], test [4]</li>
<li>fold 4 : training [1 2 3 4], test [5]</li>
<li>fold 5 : training [1 2 3 4 5], test [6]</li>
</ul>
<p>where 1,2,3,4,5,6 represents “year”.</p>Data Sciencehttps://mathsgee.com/qna/17045/what-cross-validation-technique-would-you-use-on-time-series-data-set-is-it-k-fold-or-loocv?show=17046#a17046Wed, 05 Aug 2020 06:44:25 +0000Your manager has asked you to run PCA. Would you remove correlated variables first? Why?
https://mathsgee.com/qna/17030/your-manager-has-asked-you-to-run-pca-would-you-remove-correlated-variables-first-why
You are given a data set. The data set contains many variables, some of which are highly correlated and you know about it. Your manager has asked you to run PCA. Would you remove correlated variables first? Why?Data Sciencehttps://mathsgee.com/qna/17030/your-manager-has-asked-you-to-run-pca-would-you-remove-correlated-variables-first-whyWed, 05 Aug 2020 06:29:42 +0000You came to know that your model is suffering from low bias and high variance. Which algorithm should you use to tackle it? Why?
https://mathsgee.com/qna/17029/you-came-to-know-that-your-model-is-suffering-from-low-bias-and-high-variance-which-algorithm-should-you-use-to-tackle-it-why
You came to know that your model is suffering from low bias and high variance. Which algorithm should you use to tackle it? Why?Data Sciencehttps://mathsgee.com/qna/17029/you-came-to-know-that-your-model-is-suffering-from-low-bias-and-high-variance-which-algorithm-should-you-use-to-tackle-it-whyWed, 05 Aug 2020 06:28:48 +0000Explain prior probability, likelihood and marginal likelihood in context of naiveBayes algorithm?
https://mathsgee.com/qna/17028/explain-prior-probability-likelihood-and-marginal-likelihood-in-context-of-naivebayes-algorithm
Explain prior probability, likelihood and marginal likelihood in context of naiveBayes algorithm?Data Sciencehttps://mathsgee.com/qna/17028/explain-prior-probability-likelihood-and-marginal-likelihood-in-context-of-naivebayes-algorithmWed, 05 Aug 2020 06:28:12 +0000You are given a data set on cancer detection. You’ve build a classification model and achieved an accuracy of 96%. Why shouldn’t you be happy with your model performance? What can you do about it?
https://mathsgee.com/qna/17027/you-are-given-a-data-set-on-cancer-detection-youve-build-a-classification-model-and-achieved-an-accuracy-of-96-why-shouldnt-you-be-happy-with-your-model-performance-what-can-you-do-about-it
You are given a data set on cancer detection. You’ve build a classification model and achieved an accuracy of 96%. Why shouldn’t you be happy with your model performance? What can you do about it?Data Sciencehttps://mathsgee.com/qna/17027/you-are-given-a-data-set-on-cancer-detection-youve-build-a-classification-model-and-achieved-an-accuracy-of-96-why-shouldnt-you-be-happy-with-your-model-performance-what-can-you-do-about-itWed, 05 Aug 2020 06:27:17 +0000You are given a data set. The data set has missing values which spread along 1 standard deviation from the median. What percentage of data would remain unaffected? Why?
https://mathsgee.com/qna/17026/you-are-given-a-data-set-the-data-set-has-missing-values-which-spread-along-1-standard-deviation-from-the-median-what-percentage-of-data-would-remain-unaffected-why
You are given a data set. The data set has missing values which spread along 1 standard deviation from the median. What percentage of data would remain unaffected? Why?Data Sciencehttps://mathsgee.com/qna/17026/you-are-given-a-data-set-the-data-set-has-missing-values-which-spread-along-1-standard-deviation-from-the-median-what-percentage-of-data-would-remain-unaffected-whyWed, 05 Aug 2020 06:26:37 +0000Is rotation necessary in PCA? If yes, Why? What will happen if you don’t rotate the components?
https://mathsgee.com/qna/17025/is-rotation-necessary-in-pca-if-yes-why-what-will-happen-if-you-dont-rotate-the-components
Is rotation necessary in PCA? If yes, Why? What will happen if you don’t rotate the components?Data Sciencehttps://mathsgee.com/qna/17025/is-rotation-necessary-in-pca-if-yes-why-what-will-happen-if-you-dont-rotate-the-componentsWed, 05 Aug 2020 06:25:55 +0000Your manager has asked you to reduce the dimension of this data so that model computation time can be reduced. Your machine has memory constraints. What would you do?
https://mathsgee.com/qna/17024/your-manager-has-asked-you-to-reduce-the-dimension-of-this-data-so-that-model-computation-time-can-be-reduced-your-machine-has-memory-constraints-what-would-you-do
You are given a train data set having 1000 columns and 1 million rows. The data set is based on a classification problem. Your manager has asked you to reduce the dimension of this data so that model computation time can be reduced. Your machine has memory constraints. What would you do? (You are free to make practical assumptions.)Data Sciencehttps://mathsgee.com/qna/17024/your-manager-has-asked-you-to-reduce-the-dimension-of-this-data-so-that-model-computation-time-can-be-reduced-your-machine-has-memory-constraints-what-would-you-doWed, 05 Aug 2020 06:24:58 +0000Is the Bayesian updating and/or Bayesian inference considered as a subset of machine learning or statistical learning methods ?
https://mathsgee.com/qna/17023/is-the-bayesian-updating-and-or-bayesian-inference-considered-as-a-subset-of-machine-learning-or-statistical-learning-methods
Is the Bayesian updating and/or Bayesian inference considered as a subset of machine learning or statistical learning methods ?Data Sciencehttps://mathsgee.com/qna/17023/is-the-bayesian-updating-and-or-bayesian-inference-considered-as-a-subset-of-machine-learning-or-statistical-learning-methodsWed, 05 Aug 2020 06:19:02 +0000What do you think is the single most important problem that the AI community should be working on?
https://mathsgee.com/qna/17022/what-do-you-think-is-the-single-most-important-problem-that-the-ai-community-should-be-working-on
What do you think is the single most important problem that the AI community should be working on?Artificial Intelligencehttps://mathsgee.com/qna/17022/what-do-you-think-is-the-single-most-important-problem-that-the-ai-community-should-be-working-onSun, 02 Aug 2020 21:03:57 +0000What is the most frequent metric to assess model accuracy for classification problems?
https://mathsgee.com/qna/17021/what-is-the-most-frequent-metric-to-assess-model-accuracy-for-classification-problems
What is the most frequent metric to assess model accuracy for classification problems?Data Sciencehttps://mathsgee.com/qna/17021/what-is-the-most-frequent-metric-to-assess-model-accuracy-for-classification-problemsSun, 02 Aug 2020 15:53:13 +0000Can you give some examples where both false positive and false negatives are equally important?
https://mathsgee.com/qna/17020/can-you-give-some-examples-where-both-false-positive-and-false-negatives-are-equally-important
Can you give some examples where both false positive and false negatives are equally important?Data Sciencehttps://mathsgee.com/qna/17020/can-you-give-some-examples-where-both-false-positive-and-false-negatives-are-equally-importantSun, 02 Aug 2020 15:52:42 +0000What is a Distribution of errors?
https://mathsgee.com/qna/17019/what-is-a-distribution-of-errors
What is a Distribution of errors?Data Sciencehttps://mathsgee.com/qna/17019/what-is-a-distribution-of-errorsSun, 02 Aug 2020 15:51:58 +0000What is the importance of the Median absolute deviation (MAD) ?
https://mathsgee.com/qna/17018/what-is-the-importance-of-the-median-absolute-deviation-mad
What is the importance of the Median absolute deviation (MAD) ?Data Sciencehttps://mathsgee.com/qna/17018/what-is-the-importance-of-the-median-absolute-deviation-madSun, 02 Aug 2020 15:51:18 +0000Explain about R-Squared/ Coefficient of determination.
https://mathsgee.com/qna/17017/explain-about-r-squared-coefficient-of-determination
Explain about R-Squared/ Coefficient of determination.Data Sciencehttps://mathsgee.com/qna/17017/explain-about-r-squared-coefficient-of-determinationSun, 02 Aug 2020 15:50:41 +0000What is Log-loss and how it helps to improve performance?
https://mathsgee.com/qna/17016/what-is-log-loss-and-how-it-helps-to-improve-performance
What is Log-loss and how it helps to improve performance?Data Sciencehttps://mathsgee.com/qna/17016/what-is-log-loss-and-how-it-helps-to-improve-performanceSun, 02 Aug 2020 15:47:25 +0000What do the Confusion matrix acronyms, TPR, FPR, FNR, TNR, mean?
https://mathsgee.com/qna/17015/what-do-the-confusion-matrix-acronyms-tpr-fpr-fnr-tnr-mean
What do the Confusion matrix acronyms, TPR, FPR, FNR, TNR, mean?Data Sciencehttps://mathsgee.com/qna/17015/what-do-the-confusion-matrix-acronyms-tpr-fpr-fnr-tnr-meanSun, 02 Aug 2020 15:46:40 +0000How do you determine the prior when using Bayes theorem?
https://mathsgee.com/qna/17014/how-do-you-determine-the-prior-when-using-bayes-theorem
<p>How do you determine the prior when using Bayes theorem?</p>
<p><img alt="" src="https://mathsgee.com/qna/?qa=blob&qa_blobid=5118452995297818044" style="height:370px; width:600px"></p>Data Sciencehttps://mathsgee.com/qna/17014/how-do-you-determine-the-prior-when-using-bayes-theoremSun, 02 Aug 2020 03:08:07 +0000How does one install Jupyter notebooks onto their computer?
https://mathsgee.com/qna/17013/how-does-one-install-jupyter-notebooks-onto-their-computer
How does one install Jupyter notebooks onto their computer?Data Sciencehttps://mathsgee.com/qna/17013/how-does-one-install-jupyter-notebooks-onto-their-computerSat, 01 Aug 2020 01:50:24 +0000What is Tensorflow?
https://mathsgee.com/qna/17012/what-is-tensorflow
What is Tensorflow?Data Sciencehttps://mathsgee.com/qna/17012/what-is-tensorflowSat, 01 Aug 2020 01:49:13 +0000Answered: What does the algorithm mind map say?
https://mathsgee.com/qna/17008/what-does-the-algorithm-mind-map-say?show=17009#a17009
<p>Algorithm is a set of rules that precisely defines a sequence of operations. Algorithms can perform calculation, data processing, and automated reasoning tasks.</p>
<p>Algorithms can be classified by implementation, design paradigm, optimization problems, field of study, and complexity.</p>
<p>Mind map based on <a rel="nofollow" href="https://en.wikipedia.org/wiki/Algorithm">Wikipedia: Algorithm</a> as of February 2, 2019.</p>
<p> </p>
<p>Below is the algorithm mind map:</p>
<p><img alt="" src="https://mathsgee.com/qna/?qa=blob&qa_blobid=4876093446679836777" style="height:538px; width:600px"></p>Data Sciencehttps://mathsgee.com/qna/17008/what-does-the-algorithm-mind-map-say?show=17009#a17009Thu, 30 Jul 2020 06:13:59 +0000What is dynamic programming?
https://mathsgee.com/qna/17007/what-is-dynamic-programming
What is dynamic programming?Data Sciencehttps://mathsgee.com/qna/17007/what-is-dynamic-programmingThu, 30 Jul 2020 06:12:17 +0000What is linear programming?
https://mathsgee.com/qna/17006/what-is-linear-programming
What is linear programming?Data Sciencehttps://mathsgee.com/qna/17006/what-is-linear-programmingThu, 30 Jul 2020 06:11:23 +0000What is integer programming?
https://mathsgee.com/qna/17005/what-is-integer-programming
What is integer programming?Data Sciencehttps://mathsgee.com/qna/17005/what-is-integer-programmingThu, 30 Jul 2020 06:10:51 +0000What is the maximum flow problem all about?
https://mathsgee.com/qna/17004/what-is-the-maximum-flow-problem-all-about
What is the maximum flow problem all about?Data Sciencehttps://mathsgee.com/qna/17004/what-is-the-maximum-flow-problem-all-aboutThu, 30 Jul 2020 06:10:24 +0000What is the simplex algorithm?
https://mathsgee.com/qna/17003/what-is-the-simplex-algorithm
What is the simplex algorithm?Data Sciencehttps://mathsgee.com/qna/17003/what-is-the-simplex-algorithmThu, 30 Jul 2020 06:09:37 +0000What does it mean when one approximates a target function in machine learning?
https://mathsgee.com/qna/17002/what-does-it-mean-when-one-approximates-a-target-function-in-machine-learning
What does it mean when one approximates a target function in machine learning?Data Sciencehttps://mathsgee.com/qna/17002/what-does-it-mean-when-one-approximates-a-target-function-in-machine-learningThu, 30 Jul 2020 06:07:29 +0000‘People who bought this also bought…’ recommendations seen on Amazon is based on which algorithm?
https://mathsgee.com/qna/17001/people-who-bought-this-also-bought-recommendations-seen-on-amazon-is-based-on-which-algorithm
‘People who bought this also bought…’ recommendations seen on Amazon is based on which algorithm?Data Sciencehttps://mathsgee.com/qna/17001/people-who-bought-this-also-bought-recommendations-seen-on-amazon-is-based-on-which-algorithmTue, 28 Jul 2020 11:01:26 +0000Haven’t you trained your model perfectly?
https://mathsgee.com/qna/17000/havent-you-trained-your-model-perfectly
You’re asked to build a random forest model with 10000 trees. During its training, you got training error as 0.00. But, on testing the validation error was 34.23. What is going on? Haven’t you trained your model perfectly?Data Sciencehttps://mathsgee.com/qna/17000/havent-you-trained-your-model-perfectlyTue, 28 Jul 2020 11:00:31 +0000You are asked to build a multiple regression model but your model R² isn’t as good as you wanted.
https://mathsgee.com/qna/16999/you-are-asked-to-build-a-multiple-regression-model-but-your-model-r-isnt-as-good-as-you-wanted
You are asked to build a multiple regression model but your model R² isn’t as good as you wanted. For improvement, you remove the intercept term now your model R² becomes 0.8 from 0.3. Is it possible? How?Data Sciencehttps://mathsgee.com/qna/16999/you-are-asked-to-build-a-multiple-regression-model-but-your-model-r-isnt-as-good-as-you-wantedTue, 28 Jul 2020 10:59:31 +0000Your manager has asked you to run PCA. Would you remove correlated variables first? Why?
https://mathsgee.com/qna/16998/your-manager-has-asked-you-to-run-pca-would-you-remove-correlated-variables-first-why
You are given a data set. The data set contains many variables, some of which are highly correlated and you know about it. Your manager has asked you to run PCA. Would you remove correlated variables first? Why?Data Sciencehttps://mathsgee.com/qna/16998/your-manager-has-asked-you-to-run-pca-would-you-remove-correlated-variables-first-whyTue, 28 Jul 2020 10:58:41 +0000Suppose you found that your model is suffering from low bias and high variance. Which algorithm you think could tackle this situation and Why?
https://mathsgee.com/qna/16997/suppose-you-found-that-your-model-is-suffering-from-low-bias-and-high-variance-which-algorithm-you-think-could-tackle-this-situation-and-why
Suppose you found that your model is suffering from low bias and high variance. Which algorithm you think could tackle this situation and Why?Data Sciencehttps://mathsgee.com/qna/16997/suppose-you-found-that-your-model-is-suffering-from-low-bias-and-high-variance-which-algorithm-you-think-could-tackle-this-situation-and-whyTue, 28 Jul 2020 10:58:02 +0000You are working on a time series data set. Your manager has asked you to build a high accuracy model.
https://mathsgee.com/qna/16996/you-are-working-on-a-time-series-data-set-your-manager-has-asked-you-to-build-a-high-accuracy-model
You are working on a time series data set. Your manager has asked you to build a high accuracy model. You start with the decision tree algorithm since you know it works fairly well on all kinds of data. Later, you tried a time series regression model and got higher accuracy than the decision tree model. Can this happen? Why?Data Sciencehttps://mathsgee.com/qna/16996/you-are-working-on-a-time-series-data-set-your-manager-has-asked-you-to-build-a-high-accuracy-modelTue, 28 Jul 2020 10:57:07 +0000You are given a cancer detection data set. Let’s suppose when you build a classification model you achieved an accuracy of 96%.
https://mathsgee.com/qna/16995/you-are-given-a-cancer-detection-data-set-lets-suppose-when-you-build-a-classification-model-you-achieved-an-accuracy-of-96
You are given a cancer detection data set. Let’s suppose when you build a classification model you achieved an accuracy of 96%. Why shouldn’t you be happy with your model performance? What can you do about it?Data Sciencehttps://mathsgee.com/qna/16995/you-are-given-a-cancer-detection-data-set-lets-suppose-when-you-build-a-classification-model-you-achieved-an-accuracy-of-96Tue, 28 Jul 2020 10:56:25 +0000Suppose you are given a data set which has missing values spread along 1 standard deviation from the median. What percentage of data would remain unaffected and Why?
https://mathsgee.com/qna/16994/suppose-you-are-given-a-data-set-which-has-missing-values-spread-along-1-standard-deviation-from-the-median-what-percentage-of-data-would-remain-unaffected-and-why
Suppose you are given a data set which has missing values spread along 1 standard deviation from the median. What percentage of data would remain unaffected and Why?Data Sciencehttps://mathsgee.com/qna/16994/suppose-you-are-given-a-data-set-which-has-missing-values-spread-along-1-standard-deviation-from-the-median-what-percentage-of-data-would-remain-unaffected-and-whyTue, 28 Jul 2020 10:55:36 +0000