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Machine-learning Questions Set 1:

Quiz Mode

Which of the following is an unsupervised learning technique?

PCA

Decision Tree

Naive Bayesian

Linear Regression

Solution:

Which of the following models can perform tweet classification based on the given context?

Naive Bayes

SVM

Logistic Regression

Clustering

Solution:

Which of the given functions can be used to create subsamples using a maximum dissimilarity approach?

inmaxDissim

minDissim

maxDissim

None of the above

Solution:

For which of the following hyperparameters in a decision tree algorithm is a higher value generally better?

1. Number of samples used for split

2. Depth of tree

3. Minimum samples for leaf

1 and 2

2 and 3

1, 2 and 3

None of the above

Solution:

Which of the following statements is false?

Linear Regression supports only Linear Solutions

Decision trees handles colinearity better than LR

Linear Regression is faster than KNN (K-Nearest Neighbors)

Linear Regression works better than Neural Networks when the training data is large

Solution:

What are the key assumptions made by the Naive Bayes Theorem?

The data points are numeric in nature and have zero mean

The data points are equally important and equally probable

The data points are equally probable but not necessarily equally important

The data points are equally important but not necessarily equally probable

Solution:

What is training data?

Training data is the data you use to train an algorithm or machine learning model to predict the outcome you design your model to predict

Training data is the data you use to train a blockchain to predict the outcome you design your proof of work accordingly

None of the above

Training data is the data you use to train a smart contract or chaincode to predict the outcome

Solution:

What is Computer Vision?

Computer vision is a field of Blockchain that trains computers to interpret and understand the visual world

Computer vision is a field of non-artificial intelligence that trains computers to interpret and understand the visual world

Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world

None of the above

Solution:

What is supervised learning?

Supervised learning is an approach to creating artificial intelligence, where the program is given labeled input data and the expected output results.

None of the above

Supervised learning is an approach to creating a higher consciousness, where the entity is given labeled input data and the expected output results.

Supervised learning is an approach to creating Blockchain, where the program is given labeled input data and the expected output results.

Solution:

In a highly imbalanced classification problem where the majority class accounts for 99% of the training data, which of the following statements is true?

Accuracy metric is not a good idea for imbalanced class problems, while precision and recall metrics are good.

Accuracy metric is a good idea for imbalanced class problems, and precision and recall metrics aren't good.

Accuracy metric is a good idea for imbalanced class problems, and precision and recall metrics are also good.

Accuracy metric is not a good idea for imbalanced class problems, and precision and recall metrics aren't good either.

Machine-learning Questions Set 1:

Which of the following is an unsupervised learning technique?

Solution:

Which of the following models can perform tweet classification based on the given context?

Solution:

Which of the given functions can be used to create subsamples using a maximum dissimilarity approach?

Solution:

For which of the following hyperparameters in a decision tree algorithm is a higher value generally better?

1. Number of samples used for split

2. Depth of tree

3. Minimum samples for leaf

Solution:

Which of the following statements is false?

Solution:

What are the key assumptions made by the Naive Bayes Theorem?

Solution:

What is training data?

Solution:

What is Computer Vision?

Solution:

What is supervised learning?

Solution:

In a highly imbalanced classification problem where the majority class accounts for 99% of the training data, which of the following statements is true?

Solution:

Related Question Sets:

Related Topics:

Machine-learning Questions Set 1:

Which of the following is an unsupervised learning technique?

Solution:

Which of the following models can perform tweet classification based on the given context?

Solution:

Which of the given functions can be used to create subsamples using a maximum dissimilarity approach?

Solution:

For which of the following hyperparameters in a decision tree algorithm is a higher value generally better? 1. Number of samples used for split 2. Depth of tree 3. Minimum samples for leaf

Solution:

Which of the following statements is false?

Solution:

What are the key assumptions made by the Naive Bayes Theorem?

Solution:

What is training data?

Solution:

What is Computer Vision?

Solution:

What is supervised learning?

Solution:

In a highly imbalanced classification problem where the majority class accounts for 99% of the training data, which of the following statements is true?

Solution:

Related Question Sets:

Related Topics:

For which of the following hyperparameters in a decision tree algorithm is a higher value generally better?

1. Number of samples used for split

2. Depth of tree

3. Minimum samples for leaf