A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting ...

scikit-learn comes with a few standard datasets, for instance the iris and digits datasets for classification. The iris dataset consists of measurements of three different species of irises ...

This post follows the R : Exploring Data for Machine Learning Modeling post, exploring linear model in the context of machine learning.

We'll still use the Wage dataset from the ISLR package.
This dataset reports wage and other data (age, education, jobclass, etc.) for a group of 3000 male workers in …

These are my notes on the Practical Machine Learning course (Week2: Plotting Predictors - Tutorial).

When exploring data for Machine Learning, we're looking for:

• imbalance outcomes/predictors
• outliners
• groups of outcome points not explained by any of the predictors
• skewed variables (that needs to be transformed)

We'll use the Wage dataset …