Machine Learning Random Forest with Python from Scratch - Impurity

Machine Learning Random Forest with Python from Scratch - Impurity

Assessment

Interactive Video

Information Technology (IT), Architecture

University

Hard

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The video tutorial introduces the concept of impurity in data sets, explaining its significance in decision tree building. It details how impurity is calculated, focusing on the Gini impurity index. The tutorial provides a step-by-step guide to implementing the Gini impurity calculation in code, emphasizing the importance of minimizing impurity for effective data analysis.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What is impurity in the context of a data set?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

How is impurity calculated with respect to the data set?

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

Why is it important to minimize impurity when building a decision tree?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the formula for calculating impurity mentioned in the text?

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What does the Gini impurity or Gini index represent?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

How do you implement the calculation of impurity in programming?

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

What will be studied in the next lecture after impurity?

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