Advanced Data Science Techniques in SPSS

[Language: English - Number of Lessons: 87 - Duration: 6 hours and 41 minutes - Size: 831 MB] ... 
Within days you can master some of the most complex data analysis techniques available in SPSS software. Even if you are not a professional mathematician or statistician, you will understand these techniques well and be able to apply them in practical and real situations.

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.

Advanced Data Science Techniques in SPSS

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