Q241
Open questionIn reinforcement learning, this feedback is usually called as . . . . . . . .
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Q242
Open questionIn multiclass classification number of classes must be
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Q243
Open questionWhich of the following methods can not achieve zero training error on any linearly separable dataset?
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Q244
Open questionImagine, you are solving a classification problems with highly imbalanced class. The majority class is observed 99% of times in the training data. Your model has 99% accuracy after taking the predictions on test data. Which of the following is true in such a case?
1. Accuracy metric is not a good idea for imbalanced class problems.
2.Accuracy metric is a good idea for imbalanced class problems.
3.Precision and recall metrics are good for imbalanced class problems.
4.Precision and recall metrics aren't good for imbalanced class problems.
1. Accuracy metric is not a good idea for imbalanced class problems.
2.Accuracy metric is a good idea for imbalanced class problems.
3.Precision and recall metrics are good for imbalanced class problems.
4.Precision and recall metrics aren't good for imbalanced class problems.
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Q245
Open questionWhich of the following evaluation metrics can be used to evaluate a model while modeling a continuous output variable?
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Q246
Open questionSVM is a algorithm
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Q247
Open questionWhich of the one is true about Heteroskedasticity?
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Q248
Open questionSuppose that we have N independent variables (X1, X2, Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of its variable(Say X1) with Y is -0.95. Which of the following is true for X1?
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Q249
Open questionWhile using feature selection on the data, is the number of features decreases.
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Q250
Open questionDimensionality Reduction Algorithms are one of the possible ways to reduce the computation time required to build a model
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Q251
Open questionProblem: Players will play if weather is sunny. Is this statement is correct?
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Q252
Open question. . . . . . . . allows exploiting the natural sparsity of data while extracting principal components.
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Q253
Open questionGenerally, which of the following method(s) is used for predicting continuous dependent variable?
1. Linear Regression
2. Logistic Regression
1. Linear Regression
2. Logistic Regression
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Q254
Open questionWhat is the purpose of performing cross-validation?
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Q255
Open questionIf X and Y in a regression model are totally unrelated,
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Q256
Open questionHow can SVM be classified?
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Q257
Open questionA company has build a kNN classifier that gets 100% accuracy on training data. When they deployed this model on client side it has been found that the model is not at all accurate. Which of the following thing might gone wrong? Note: Model has successfully deployed and no technical issues are found at client side except the model performance
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Q258
Open questionwhich of the following cases will K-Means clustering give poor results?
1. Data points with outliers
2. Data points with different densities
3. Data points with round shapes
4. Data points with non-convex shapes
1. Data points with outliers
2. Data points with different densities
3. Data points with round shapes
4. Data points with non-convex shapes
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Q259
Open questionWhich of the following option is / are correct regarding benefits of ensemble model?
1. Better performance
2. Generalized models
3. Better interpretability
1. Better performance
2. Generalized models
3. Better interpretability
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Q260
Open questionA multiple regression model has the form: y = 2 + 3x1 + 4x2. As x1 increases by 1 unit (holding x2 constant), y will
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