June 2018
Intermediate to advanced
276 pages
6h 26m
English
Content preview from Mastering Machine Learning for Penetration Testing
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Chapter 3 – Malware Detection with API Calls and PE Headers
- Load the dataset using the pandas python library, and this time, add the low_memory=False parameter. Search for what that parameter does.
df = pd.read_csv(file_name, low_memory=False)
- Prepare the data that will be used for training.
original_headers = list(df.columns.values)total_data = df[original_headers[:-1]]total_data = total_data.as_matrix()target_strings = df[original_headers[-1]]
- Split the data with the test_size=0.33 parameter.
train, test, target_train, target_test = train_test_split(total_data, target_strings, test_size=0.33, random_state=int(time.time()))
- Create a set of classifiers that contains DecisionTreeClassifier(), RandomForestClassifier(n_estimators=100) ...
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