Data Shaping and best practices.

Overview

In this article we will using Audiology dataset from UCL machine learning repository to build our machine learning model ground up. During the course of building the model we will learning how to do, label filtering, feature mapping, imputing missing values, standardize our datasets and finally principle component analysis for dimensionality reduction. After doing all those for our datasets we will feed those data to different machine learning algorithms and compare the accuracy of the output.

Label filter


Feature Mapping


Imputing missing values


Standardize


Dimension reduction via Principle component Analysis and Rest