Mineral Resource Clustering Analysis Using Random Forest Classification

Overview This analysis applies multivariate statistical techniques to uncover patterns and relationships within mineral reosurce datasets. The dataset encompasses multiple features including voltage (V), altitude (H), soil type (S), and mineral type (M). A Random Forest classifier serves as the primary predictive model, leveraging ensemble lear ...

Posted on Sat, 06 Jun 2026 18:29:05 +0000 by tauchai83

Analyzing Athlete Injury Prediction Data with Python

To explore the relationship between athlete attrbiutes and injury likelihood, we first examine age, weight, and height using data aggregation and visualization. Analyzing by Age Groups Method 1: Pivot Table age_df = pd.pivot_table(df, values='Recovery_Time', index='Player_Age', columns='Likelihood_of_Injury', aggfunc='count') # Rename columns ...

Posted on Fri, 15 May 2026 01:59:52 +0000 by cneumann