NBA Points, Assists, and Rebounds (PAR) Prediction using NumPy, Linear Regression, and Polynomials
This Python script, created by GPT-4, predicts the next numbers in sequences representing NBA Points, Assists, and Rebounds (PAR) using NumPy, Linear Regression, and PolynomialFeatures from scikit-learn. The script demonstrates how to prepare data, train a Linear Regression model with Polynomial Features, and make predictions for the next values in each of the given sequences.
The model can be easily adapted for other sports or sequences by modifying the input data in the sequences variable. The current input sequences represent NBA PAR, but you can replace them with any other numerical sequences to make predictions in different contexts.
Key features:
Created by GPT-4
Utilizes NumPy, scikit-learn's Linear Regression, and PolynomialFeatures
Predicts the next numbers in NBA Points, Assists, and Rebounds (PAR) sequences
Easily adaptable for other sports or numerical sequences
With this simple and efficient script, users can predict the next values in various sports-related or other numerical sequences, demonstrating the versatility of the Linear Regression model combined with Polynomial Features. DYOR. Use at your own risk. NFA.