What is outlier detection in machine learning?

What is outlier detection in machine learning?

Outlier detection is the process of identifying data points that differ significantly from the majority of the data.

Why is it important to detect outliers?

Detecting outliers is crucial as they can skew results, affect model performance, and lead to incorrect conclusions.

What are some common methods for outlier detection?

Common methods include Z-score, IQR (Interquartile Range), and machine learning techniques like Isolation Forest.

Can you show me a Python example for outlier detection?

Sure! Here's a simple example using the IQR method in Python:

import numpy as np
import pandas as pd

data = pd.DataFrame({'values': [10, 12, 12, 13, 12, 100]})
Q1 = data['values'].quantile(0.25)
Q3 = data['values'].quantile(0.75)
IQR = Q3 - Q1
outliers = data[(data['values'] < (Q1 - 1.5 * IQR)) | (data['values'] > (Q3 + 1.5 * IQR))]
print(outliers)