32.579 texts in total, 14.012 NOT hateful texts and 18.567 HATEFUL texts All duplicate values were removed Split using sklearn into 80% train and 20% temporary test (stratified label). Then split the test set using 0.50% test and validation (stratified label) Split: 80/10/10 Train set label distribution: 0 ==> 11.210, 1 ==> 14.853, 26.063 in total Validation set label distribution: 0 ==> 1.401, 1 ==> 1.857, 3.258 in total Test set label distribution: 0 ==> 1.401, 1 ==> 1.857, 3.258 in… See the full description on the dataset page: https://huggingface.co/datasets/christinacdl/hate_speech_dataset.

Purpose of this data is Linear Regression

Handling categorical features in a scikit-learn model. Carrying out a train/test split. Training a model. Evaluating that model on the testing data.

The mpg data set represents the fuel economy (in miles per gallon) for 38 popular models of car, measured between 1999 and 2008.

Factor Type Description manufacturer multi-valued discrete Vehicle manufacturer model multi-valued discrete Model of the vehicle displ continuous Size of engine [litres] year multi-valued discrete Year of vehicle manufacture cyl multi-valued discrete Number of ignition cylinders trans multi-valued discrete Transmission type (manual or automatic) drv multi-valued discrete Driven wheels (f=front, 4=4-wheel, r=rear wheel drive) city continuous Miles per gallon, city driving conditions (fuel economy) hwy continuous Miles per gallon, highway driving conditions (fuel economy) fl multi-valued discrete Vehicle type class multi-valued discrete Vehicle class (suv, compact, etc)