Supervised Learning

This repository explores Supervised learning algorithms for classification and regression problems.

Supervised Learning Algorithms

1. Gaussian Naive Bayes
2. Support Vector Machines
3. Decision Trees
4. Random Forests
5. k-Nearest Neighbours
6. Linear Regression

Dataset for Regression Algorithms: "house_price" dataset:

https://www.kaggle.com/harlfoxem/housesalesprediction

Attributes Information (total features = 19):

1. id: notation for house
2. date: date house was sold
3. sqft_living: square footage of house
4. bedrooms: number of bedrooms
5. price: house price (prediction target) and so on...

Dataset for Classification Algorithms: "iris" dataset:

https://archive.ics.uci.edu/ml/machine-learning-databases/iris/

Attributes Information (total features = 4):

1. sepal length in cm
2. sepal width in cm
3. petal length in cm
4. petal width in cm
5. classes:
   1. Iris Setosa
   2. Iris Versicolour
   3. Iris Virginica