Ensemble Machine Learning Techniques 3.3: Making Predictions on Movie Ratings Using SVM

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Information Technology (IT), Architecture, Social Studies
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University
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary objective when using the IMDB dataset in this tutorial?
To predict the average IMDB score of a movie
To find the release year of a movie
To determine the budget of a movie
To predict the genre of a movie
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which library is used for encoding categorical data in this tutorial?
Pandas
NumPy
SKlearn
Matplotlib
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is it important to convert categorical data into numeric form for SVM?
It reduces the size of the dataset
It improves the accuracy of the model
Numeric data is easier to visualize
SVM can only process numeric data
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the initial performance result of a single SVM classifier in this tutorial?
0.9
0.7
0.5
0.2
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main purpose of the bagging algorithm?
To simplify the model training process
To reduce the dataset size
To increase the number of features
To improve model accuracy by combining results from multiple models
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which function is used to combine results from different models in the bagging implementation?
Subsample
StandardScaler
TrainTestSplit
BaggingPredict
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is suggested to try after implementing bagging with SVM?
Reducing the number of features
Increasing the number of estimators
Implementing a decision tree algorithm
Using a larger dataset
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