Install them:
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print(df.info()) print(df.describe())
Convert unreadable binary files into human-readable formats (like .txt or .json). Install them: Are you looking to , dig
from mlxtend.frequent_patterns import apriori, association_rules # Assumes transactional data is one-hot encoded into a boolean matrix frequent_itemsets = apriori(df_transactional, min_support=0.05, use_colnames=True) rules = association_rules(frequent_itemsets, metric="lift", min_threshold=1.2) # Sort rules to find the highest-confidence product bundles top_rules = rules.sort_values(by="confidence", ascending=False) Use code with caution. 5. Model Evaluation and Validation Install them: Are you looking to
model = DecisionTreeClassifier() model.fit(X_train, y_train)