Supervised learning and unsupervised clustering both require at least one
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Computer Science · all questionsMachine Learning
Machine Learning
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Which of the following sentences are correct in reference to Information gain? a. It is biased towards single-valued attributes b. It is biased towards multi-valued attributes c. ID3 makes use of information gain d. The approact used by ID3 is greedy
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Even if there are no actual supervisors . . . . . . . . learning is also based on feedback provided by the environment
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A feature F1 can take certain value: A, B, C, D, E & F and represents grade of students from a college. Which of the following statement is true in following case?
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When it is necessary to allow the model to develop a generalization ability and avoid a common problem called . . . . . . . .
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Which of the following is true about Manhattan distance?
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Suppose, you have 2000 different models with their predictions and want to ensemble predictions of best x models. Now, which of the following can be a possible method to select the best x models for an ensemble?
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In a linear regression problem, we are using "R-squared" to measure goodness-of-fit. We add a feature in linear regression model and retrain the same model. Which of the following option is true?
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True or False: Ensemble of classifiers may or may not be more accurate than any of its individual model.
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In terms of bias and variance. Which of the following is true when you fit degree 2 polynomial?
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Which of the following assumptions do we make while deriving linear regression parameters?
1. The true relationship between dependent y and predictor x is linear
2. The model errors are statistically independent
3. The errors are normally distributed with a 0 mean and constant standard deviation
4. The predictor x is non-stochastic and is measured error-free
1. The true relationship between dependent y and predictor x is linear
2. The model errors are statistically independent
3. The errors are normally distributed with a 0 mean and constant standard deviation
4. The predictor x is non-stochastic and is measured error-free
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For the given weather data, Calculate probability of not playing
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In PCA the number of input dimensiona are equal to principal components
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What are the two methods used for the calibration in Supervised Learning?
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A student Grade is a variable F1 which takes a value from A,B,C and D. Which of the following is True in the following case?
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Regression trees are often used to model . . . . . . . . data.
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Support Vector Machine is
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Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of it's hyper parameter.What would happen when you use very large value of C(C->infinity)?
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In SVR we try to fit the error within a certain threshold.
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Q100
Open questionWhich of the following are correct statement(s) about stacking?
1. A machine learning model is trained on predictions of multiple machine learning models
2. A Logistic regression will definitely work better in the second stage as compared to other classification methods
3. First stage models are trained on full / partial feature space of training data.
1. A machine learning model is trained on predictions of multiple machine learning models
2. A Logistic regression will definitely work better in the second stage as compared to other classification methods
3. First stage models are trained on full / partial feature space of training data.
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