Fading Coder

One Final Commit for the Last Sprint

Implementing a Stock Trend Classifier with PySpark and Random Forest

Objective Definition The goal of this implementation is to predict the directional movement of a stock's closing price based on daily financial metrics. The target variable is binary: a label of 1 indicates a non-negative price change (Change >= 0), while 0 indicates a negative change (Change < 0)....

Implementing Machine Learning with Random Forest Models in Python

Overview of Random Forest Random forest is an ensemble learning method suited for both classification and regression tasks. It operates by constructing multiple decision trees during training and merging their outputs for more robust predictions. Applicability Classification: Medical diagnosis, imag...

Predicting Passenger Survival on the Titanic Using Ensemble Methods

Import the necessary libraries to data manipulation, visualization, and machine learning: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns from scipy.stats import chi2_contingency from sklearn.ensemble import RandomForestClassifier from sklearn.model_selec...