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Session: Regressions Regression Algorithms Linear Regression Logistic Regression Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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Regressions è Regression Algorithms Linear Regression Logistic Regression Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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© 2017 ElephantScale.com. All rights reserved. What is Regression Analysis u Regression models relationship between independent variable(s) (predictor) and dependent variable (target) u Regressions are used to predict 'numeric' data – House prices – Stock price 3 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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© 2017 ElephantScale.com. All rights reserved. Regression Algorithms Algorithm Description Use Case Linear Regression Establishes a best fit 'straight line' Advantages: - Simple, well understood - Scales to large datasets Disadvantages - Prone to outliers - House prices - Stock market Logistic Regression - Calculates the probability of outcome (success or failure) - Used for 'classification' J - Needs large sample sizes for accurate prediction - Mortgage application approval 4 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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© 2017 ElephantScale.com. All rights reserved. Regression Algorithms Algorithm Description Use Case Polynomial Regression If power of independent variable is more than 1. Y = a + b * X 2 - Can be prone to overfitting - Results can be hard to explain Stepwise Regression - When we have multiple independent variables, automatically selects significant variables - No human intervention - AIC - House price predictor 5 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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© 2017 ElephantScale.com. All rights reserved. Regression Algorithms Algorithm Description Use Case Ridge Regression - used when independent variables are highly correlated - Uses L2 regularization Lasso Regression - Uses L1 regularization ElasticNet Regression - Hybrid of Lasso and Ridge regressions 6 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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Linear Regression Regression Algorithms è Linear Regression Logistic Regression Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20 Licensed for personal use only for Sriram Anne <[email protected]> from Python @ Macy's 2018-02-20 @ 2018-02-20
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© 2017 ElephantScale.com. All rights reserved.
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