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Machine Learning

27

Jan'17

203.4.7 Cross Validation

Choosing Optimal Model In previous section, we studied about Model-Bias Variance Tradeoff Unfortunately there is no scientific method of choosing …

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27

Jan'17

203.4.6 Model-Bias Variance Tradeoff

Model Bias and Variance In previous section, we studied about Type of Datasets, Type of Errors and Problem of Overfitting …

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27

Jan'17

203.4.5 Type of Datasets, Type of Errors and Problem of Overfitting

The Problem of Over Fitting In previous section, we studied about What is a Best Model? In search of the …

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27

Jan'17

203.4.4 What is a Best Model?

What is a best model? How to build? In previous section, we studied about ROC and AUC A model with …

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27

Jan'17

203.4.3 ROC and AUC

ROC Curve – Interpretation In previous section, we studied about  Calculating Sensitivity and Specificity in R How many mistakes are …

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27

Jan'17

203.4.2 Calculating Sensitivity and Specificity in R

Calculating Sensitivity and Specificity In previous section, we studied about  Model Selection and Cross Validation Building Logistic Regression Model Fiberbits …

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