Advanced Data Science Techniques in SPSS
Let’s see what you will learn: Stepwise regression + Non-linear regression + K nearest neighbor + Decision trees + Neural networks + Two-stage cluster analysis + Survival analysis.
What you will learn in this course? Perform advanced linear regression using predictive selection techniques + Perform any type of non-linear regression analysis + Prediction using the k nearest neighbor (KNN) technique. + Using binary trees (CART) for prediction (both regression and classification trees) + Using non-binary (CHAID) trees for prediction (both regression and classification trees) + Construction and training of a multilayer perceptron (MLP) + Construction and training of a radial basis neural network (RBF) + Perform two-way clustering analysis + Carrying out survival analysis using the Kaplan-Meier method + Performing survival analysis using Cox regression + Validation of prediction techniques (KNN, trees, neural networks) using validation set and cross-validation approach + Save a predictive analytics model and use it to predict future new data.
