/UCI-HAR-Dataset-Model-Training-and-Testing-Accuracy

A code to train and evaluate Human Activity Recognition Using SmartPhone dataset

Primary LanguageJupyter Notebook

UCI-HAR-Dataset-Model-Training-and-Testing-Accuracy

I used SVM to train and evaluate Human Activity Recognition Using SmartPhone dataset. The main dataset can be found here: https://archive.ics.uci.edu/ml/datasets/human+activity+recognition+using+smartphones#

Language: Python Medium: Jupyter Notebook Algorithm: SVM Kernels: Linear, RBF, Polynomial and Sigmoid. Used Modules: scikit-learn, pandas, numpy, matplotlib, seaborn.