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Course Details –:
- Perform advanced linear regression using predictor selection techniques
- Perform any type of nonlinear regression analysis
- Make predictions using the k nearest neighbor (KNN) technique
- Use binary (CART) trees for prediction (both regression and classification trees)
- Use non-binary (CHAID) trees for prediction (both regression and classification trees)
- Build and train a multilayer perceptron (MLP)
- Build and train a radial basis funcion (RBF) neural network
- Perform a two-way cluster analysis
- Run a survival analysis using the Kaplan-Meier method
- Run a survival analysis using the Cox regression
- Validate the predictive techniques (KNN, trees, neural networks) using the validation set approach and the cross-validation
- Save a predictive analysis model and use it for predictions on future new data
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