`the purpose was to use fuzzy decision tree to predict future stock market price and relevant information retrieval for the stock. step are i. Fuzzification ii. Tree construction iii. Defuzzification
This are some of my code.
your textfuzzy_sets = {}
your textfor feature in feature_names:
your textfeature_values = X[feature].values
your textfuzzy_sets[feature] = {}
your textfuzzy_sets[feature]['low'] = fuzz.trimf(feature_values, your text[np.min(feature_values), np.min(feature_values), your textnp.mean(feature_values)])
your textfuzzy_sets[feature]['medium'] = fuzz.trimf(feature_values, your text[np.min(feature_values), np.mean(feature_values), your textnp.max(feature_values)])
your textfuzzy_sets[feature]['high'] = fuzz.trimf(feature_values, [np.mean(feature_values), np.max(feature_values), np.max(feature_values)])
your text# Create fuzzy membership functions for the target variable
your texttarget_values = y.values
your textfuzzy_sets[target_name] = {}
your textfuzzy_sets[target_name]['low'] = fuzz.trimf(target_values, your text[np.min(target_values), np.min(target_values), np.mean(target_values)])
your textfuzzy_sets[target_name]['medium'] = fuzz.trimf(target_values, your text[np.min(target_values), np.mean(target_values), np.max(target_values)])
your textfuzzy_sets[target_name]['high'] = fuzz.trimf(target_values, your text[np.mean(target_values), np.max(target_values), np.max(target_values)])
text# Create fuzzy membership functions for the target variable
your texttarget_values = y.values
your textfuzzy_sets[target_name] = {}
your textfuzzy_sets[target_name]['low'] = fuzz.trimf(target_values, your text[np.min(target_values), np.min(target_values), np.mean(target_values)])
your textfuzzy_sets[target_name]['medium'] = fuzz.trimf(target_values, your text[np.min(target_values), np.mean(target_values), np.max(target_values)])
your textfuzzy_sets[target_name]['high'] = fuzz.trimf(target_values, your text[np.mean(target_values), np.max(target_values), np.max(target_values)])
your text# Create the fuzzy decision tree
your textfuzzy_tree = {}
your textfor feature in feature_names:
your textfuzzy_tree[feature] = your textctrl.Antecedent(np.arange(np.min(X[feature]), np.max(X[feature]), your textnp.mean(X[feature])), feature)
your textfor fuzzy_set in fuzzy_sets[feature]:
your textfuzzy_tree[feature][fuzzy_set] = your textfuzz.trimf(fuzzy_tree[feature].universe, fuzzy_sets[feature][fuzzy_set])
your texttarget_variable = ctrl.Consequent(np.arange(np.min(y), np.max(y), your textnp.mean(y)), target_name)
your textfor fuzzy_set in fuzzy_sets[target_name]:
your texttarget_variable[fuzzy_set] = your textfuzz.trimf(target_variable.universe, fuzzy_sets[target_name][fuzzy_set])
your text# Print the fuzzy decision tree
your textprint("Fuzzy Decision Tree:")
your textprint(fuzzy_tree)
your textprint(target_variable)
your textBut i keep getting error message in the process of creating the tree`