Predictive Analytics with TensorFlow 5.2: Using kNN for Predictive Analytics
Interactive Video
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Information Technology (IT), Architecture
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University
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Practice Problem
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Hard
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What type of learning algorithm is KNN?
Reinforcement learning
Semi-supervised learning
Supervised learning
Unsupervised learning
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a common application of KNN?
Image generation
Genetic expression profiling
Data compression
Economic forecasting
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In KNN, what is the primary goal when using a labeled dataset?
To generate new data
To reduce dimensionality
To predict labels from features
To cluster data points
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of Min-Max scaling in KNN implementation?
To normalize features within a specific range
To enhance feature correlation
To increase the dataset size
To remove outliers
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which distance metric is used in the example implementation of KNN?
Euclidean distance
Manhattan distance
Hamming distance
Cosine similarity
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of the hyperparameter 'K' in KNN?
It specifies the batch size
It defines the learning rate
It sets the number of nearest neighbors considered
It determines the number of features
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Why is accuracy not a significant metric for evaluating KNN in this context?
Because accuracy is always low for KNN
Because KNN is not a classification algorithm
Because the dataset is too small
Because the task involves predicting continuous values
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