FinTech 11-2 Classification

FinTech 11-2 Classification

Professional Development

10 Qs

quiz-placeholder

Similar activities

Kuis Praktik baik pembelajaran berdiferensiasi

Kuis Praktik baik pembelajaran berdiferensiasi

Professional Development

10 Qs

DASETERA

DASETERA

Professional Development

10 Qs

Quiz Pembatik Level 2

Quiz Pembatik Level 2

Professional Development

10 Qs

Digital test

Digital test

Professional Development

10 Qs

Friday Fun

Friday Fun

Professional Development

10 Qs

QM ISO - Q3 Activity

QM ISO - Q3 Activity

Professional Development

10 Qs

Agency OBX -Day 1 Quiz

Agency OBX -Day 1 Quiz

Professional Development

15 Qs

FinTech 11-2 Classification

FinTech 11-2 Classification

Assessment

Quiz

Computers, Other

Professional Development

Hard

Created by

Louis Burns

Used 20+ times

FREE Resource

AI

Enhance your content in a minute

Add similar questions
Adjust reading levels
Convert to real-world scenario
Translate activity
More...

10 questions

Show all answers

1.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

Which were the objectives for Classification day 2?

Feature engineering categorical features

Robust hyperparameter tuning

Decision trees and random forests

Boosting and bagging

2.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

Which are ensemble learning algorithms?

Logistic regression

Random forrests

Decision trees

Gradient boosted trees

3.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

Which functions might we use for preprocessing categorical data?

get_dummies()

to_string()

StandardScaler()

LabelEncoder()

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which model is it helpful to visualize?

Logistic regression

Random forrests

Decision trees

Support vector machine

5.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

What can you learn from the decision tree visualization?

How many nodes and branches the model has.

How deep the tree goes.

How accurate the model is.

Whether the model might be overfitting.

6.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

Which models use weak learners?

Random Forests

Decision Tree

XGBoost

Support Vector Machines

7.

MULTIPLE SELECT QUESTION

30 sec • 1 pt

What are ways to improve the performance of random forests?

Increase the number of estimators

Additional feature engineering

Change the random state

Use gradient boosting (XGBoost)

Access all questions and much more by creating a free account

Create resources

Host any resource

Get auto-graded reports

Google

Continue with Google

Email

Continue with Email

Classlink

Continue with Classlink

Clever

Continue with Clever

or continue with

Microsoft

Microsoft

Apple

Apple

Others

Others

Already have an account?