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Machine Learning for Cybersecurity Cookbook
book

Machine Learning for Cybersecurity Cookbook

by Emmanuel Tsukerman
November 2019
Intermediate to advanced content levelIntermediate to advanced
346 pages
9h 36m
English
Packt Publishing
Content preview from Machine Learning for Cybersecurity Cookbook

How to do it…

In the following steps, we will build an example-dependent, cost-sensitive classifier using the costcla library on credit card transaction data:

  1. Import pandas and read the data pertaining to transactions into a data frame:
import pandas as pdfraud_df = pd.read_csv("FinancialFraudDB.csv", index_col=None)
  1. Set a cost to false positives and false negatives:
card_replacement_cost = 5customer_freeze_cost = 3
  1. Define a cost matrix corresponding to the figure:
import numpy as npcost_matrix = np.zeros((len(fraud_df.index), 4))cost_matrix[:, 0] = customer_freeze_cost * np.ones(len(fraud_df.index))cost_matrix[:, 1] = fraud_df["Amount"].valuescost_matrix[:, 2] = card_replacement_cost * np.ones(len(fraud_df.index))
  1. Create labels and ...
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Publisher Resources

ISBN: 9781789614671Supplemental Content