PCA-on-Breast-Cancer-Data

Principal Component Analysis Example Notebook

PCA(Principal Component Analysis)

It is not an algorithm of machine learning. It is just a technique of dimensionality reduction(From multiple number of independent features to less number of independent features) using new vector space. The reason is that more dimensions may lead the dataset to suffer from underfitting.

Dataset Key Description

data: stores data
target:for output (0 for one class and 1 for other)
target_names: names of two different types of targets
DESCR: Description of data
feature_names: name of columns in dataset

The difference between values in multiple columns is very very high. So, to normalize or scale it, minmaxscaler is used.
Then the data is plotted with the help of target values.