Untitled

import pandas as pd
from sys import exit

def candidate_elimination(data):
    specific_hypothesis = ['0'] * (data.shape[1] - 1)
    general_hypothesis = [['?'] * (data.shape[1] - 1)]

    for index, row in data.iterrows():
        if row['Play'] == 'Yes':
            for i in range(len(specific_hypothesis)):
                if specific_hypothesis[i] == '0':
                    specific_hypothesis[i] = row.iloc[i]
                elif specific_hypothesis[i] != row.iloc[i]:
                    specific_hypothesis[i] = '?'

            general_hypothesis = [
                g for g in general_hypothesis if all(
                    g[i] == '?' or g[i] == row.iloc[i] or specific_hypothesis[i] == '?' for i in range(len(g))
                )
            ]
        else:
            new_general_hypothesis = []
            for i in range(len(specific_hypothesis)):
                if specific_hypothesis[i] == '?':
                    continue
                elif specific_hypothesis[i] != row.iloc[i]:
                    new_hypothesis = specific_hypothesis.copy()
                    new_hypothesis[i] = '?'
                    new_general_hypothesis.append(new_hypothesis)

            general_hypothesis.extend([
                h for h in new_general_hypothesis if all(
                    h[j] == '?' or h[j] == row.iloc[j] or specific_hypothesis[j] == '?' for j in range(len(h))
                )
            ])

    general_hypothesis = [
        g for g in general_hypothesis if not any(
            all(g[i] == '?' or g[i] == other[i] for i in range(len(g))) and g != other for other in general_hypothesis
        )
    ]

    return specific_hypothesis, general_hypothesis


file_path = r'D:/5f7/training_data.csv'

try:
    data = pd.read_csv(file_path)
except FileNotFoundError:
    print(f"Error: File not found at {file_path}")
    exit()

required_columns = ['Outlook', 'Temperature', 'Humidity', 'Wind', 'Play']
if not all(column in data.columns for column in required_columns):
    print("Error: The dataset must include the following columns: ")
    print(required_columns)
    exit()

specific_hypothesis, general_hypothesis = candidate_elimination(data)
print("Specific Hypothesis: ", specific_hypothesis)
print("General Hypothesis: ", general_hypothesis)