Random Forest Example

 Creating a Random Forest: Steps

Bootstrapped Dataset

           The bootstrap method is a resampling technique used to estimate statics on a population by sampling a dataset with Replacement. It can be used to estimate summary statistics such as the mean or standard deviation.

The bootstrap dataset (Same size as original) is created by randomly selecting samples from the original dataset. Following is our sample dataset.

Family History

High BP

Overweight

Weight (Kg)

Diabetes

No

No

No

65

No

Yes

Yes

Yes

100

Yes

Yes

Yes

No

75

No

Yes

No

Yes

110

Yes

•      Step 1: Create a Bootstrap Dataset


•      Step 2: Creating Decision Tree: Bootstrapped dataset 






•      Step 3 & 4: Counting the votes for Predicting 

•      How good is your model: Bootstrapped Dataset 






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