Q261
Open questionTrue or False: Ensembles will yield bad results when there is significant diversity among the models. Note: All individual models have meaningful and good predictions.
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Computer Science · all questionsMachine Learning
Machine Learning
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Q262
Open questionWhich of the following is / are true about weak learners used in ensemble model?
1. They have low variance and they don't usually overfit
2. They have high bias, so they can not solve hard learning problems
3. They have high variance and they don't usually overfit
1. They have low variance and they don't usually overfit
2. They have high bias, so they can not solve hard learning problems
3. They have high variance and they don't usually overfit
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Q263
Open questionAccording to . . . . . . . . , it's a key success factor for the survival and evolution of all species.
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Q264
Open questionIn a Rule based classifier, If there is a rule for each combination of attribute values, what do you called that rule set R
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Q265
Open questionWhich of the following classifications would best suit the student performance classification systems?
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Q266
Open questionWhich of the following sentence is FALSE regarding regression?
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Q267
Open questionGiven a rule of the form IF X THEN Y, rule confidence is defined as the conditional probability that Select one:
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Q268
Open questionDatabase query is used to uncover this type of knowledge.
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Q269
Open questionA measurable property or parameter of the data-set is
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Q270
Open questionLet's say, you are working with categorical feature(s) and you have not looked at the distribution of the categorical variable in the test data. You want to apply one hot encoding (OHE) on the categorical feature(s). What challenges you may face if you have applied OHE on a categorical variable of train dataset?
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Q271
Open questionSuppose 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 small C (C~0)?
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Q272
Open questionWhich of the following is a reasonable way to select the number of principal components "k"?
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Q273
Open questionIf you need a more powerful scaling feature, with a superior control on outliers and the possibility to select a quantile range, there's also the class . . . . . . . .
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Q274
Open questionLinear SVMs have no hyperparameters that need to be set by cross-validation
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Q275
Open questionImpact of high variance on the training set ?
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Q276
Open questionWhich of the following are components of generalization Error?
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Q277
Open questionWhich statement is true about neural network and linear regression models?
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Q278
Open questionWhat are support vectors?
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Q279
Open questionWhich of the following can act as possible termination conditions in K-Means?
1. For a fixed number of iterations.
2. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum.
3. Centroids do not change between successive iterations.
4. Terminate when RSS falls below a threshold.
1. For a fixed number of iterations.
2. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum.
3. Centroids do not change between successive iterations.
4. Terminate when RSS falls below a threshold.
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Q280
Open questionClassification rules are extracted from . . . . . . . .
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