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. TIMESTAMP 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 The post Machine Learning in R: Building a Classification Model appeared first on Data Science PR. Originally from Machine Learning & AI – Data Science PR https://ift.tt/3hISR2O
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