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Machine Learning in R: Building a Classification Model

In this video, I cover the concepts and practical aspects of building a classification model using the R programming language; starting from loading in the iris dataset, splitting the dataset, building the training model and cross-validation models using support vector machine, evaluating the prediction performance as well as the feature importance.


0:39 Download code from Data Professor GitHub

0:48 Import Iris dataset 0:59 Check for missing values

1:56 Data splitting 2:57 Data splitting in R

5:28 Practice: Make scatter plot comparing Training and Testing sets (distribution)

7:35 Mean centering

11:16 Building Training and CV models in R

15:38 Model performance metrics

16:54 Feature importance

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