Difference between revisions of "TDSM 7.23"
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Anjul.tyagi (talk | contribs) (Created page with "The correlation coeff. will show how each metric is related to the final results. We can use feature selection to see how effective a feature is in predicting the results. Som...") |
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The correlation coeff. will show how each metric is related to the final results. We can use feature selection to see how effective a feature is in predicting the results. Some feature selection algorithms are Linear Regression, Random-Forest and Randomised Lasso. | The correlation coeff. will show how each metric is related to the final results. We can use feature selection to see how effective a feature is in predicting the results. Some feature selection algorithms are Linear Regression, Random-Forest and Randomised Lasso. | ||
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| + | Also, it is important to combine the predictive power with certain problem. For example, when we predict earthquake, we expect to enhance the recall of the model. However, when we predict terrorist, precision plays a more important role. | ||
Latest revision as of 20:11, 11 December 2017
The correlation coeff. will show how each metric is related to the final results. We can use feature selection to see how effective a feature is in predicting the results. Some feature selection algorithms are Linear Regression, Random-Forest and Randomised Lasso.
Also, it is important to combine the predictive power with certain problem. For example, when we predict earthquake, we expect to enhance the recall of the model. However, when we predict terrorist, precision plays a more important role.
