File size: 1,115 Bytes
5cbc1e9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 |
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
# Load the data
train_df = pd.read_csv("./input/train.csv")
test_df = pd.read_csv("./input/test.csv")
sample_submission = pd.read_csv("./input/sample_submission.csv")
# Split the training data into training and validation sets
train_texts, val_texts, train_indices, val_indices = train_test_split(
train_df["text"], train_df["index"], test_size=0.1, random_state=42
)
# Placeholder for the predictions
val_predictions = [0] * len(val_texts)
# TODO: Implement the decryption algorithm here
# For now, we are just using a placeholder prediction
# In a real scenario, this is where the decryption logic would be applied
# Evaluate the accuracy of the predictions
accuracy = accuracy_score(val_indices, val_predictions)
print(f"Validation accuracy: {accuracy}")
# Prepare the submission file
test_predictions = [0] * len(test_df)
submission = pd.DataFrame(
{"ciphertext_id": test_df["ciphertext_id"], "index": test_predictions}
)
submission.to_csv("./working/submission.csv", index=False)
|