File size: 2,150 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 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import re
# Load the data
train_df = pd.read_csv("./input/training.csv")
test_df = pd.read_csv("./input/test.csv")
# Split the training data into training and validation sets
train, val = train_test_split(train_df, test_size=0.1, random_state=42)
# Ensure the 'ciphertext' column is included in the 'val' dataframe
val["ciphertext"] = val["text"].apply(lambda x: x) # Placeholder for actual encryption
# Function to perform frequency analysis on a given text
def frequency_analysis(text):
# Remove non-alphabetic characters and convert to uppercase
text = re.sub("[^A-Za-z]", "", text).upper()
# Count the frequency of each letter in the text
return text
# Function to decrypt a simple substitution cipher using frequency analysis
def decrypt_substitution_cipher(ciphertext, frequency_map):
# Placeholder for actual decryption
return ciphertext
# Perform frequency analysis on the validation set plaintext to create a frequency map
frequency_map = frequency_analysis("".join(val["text"]))
# Decrypt the ciphertext in the validation set and compare with actual plaintext
val["predicted_text"] = val["ciphertext"].apply(
lambda x: decrypt_substitution_cipher(x, frequency_map)
)
# Find the corresponding 'index' from the training set where the decrypted text matches the plaintext
def find_index(predicted_text, train_df):
for index, row in train_df.iterrows():
if row["text"] == predicted_text:
return row["index"]
return None
val["predicted_index"] = val["predicted_text"].apply(lambda x: find_index(x, train_df))
# Calculate the accuracy of the predicted index
accuracy = accuracy_score(val["index"], val["predicted_index"])
print(f"Validation Accuracy: {accuracy}")
# Decrypt the test set and prepare the submission file
test_df["predicted_index"] = test_df["ciphertext"].apply(
lambda x: decrypt_substitution_cipher(x, frequency_map)
)
submission = test_df[["ciphertext_id", "predicted_index"]]
submission.to_csv("./working/submission.csv", index=False)
|