Computer Science · all questions

Machine Learning
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Q281

The cost parameter in the SVM means:

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Q282

his clustering approach initially assumes that each data instance represents a single cluster.

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Q283

A supervised scenario is characterized by the concept of a . . . . . . . .

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Q284

Which of the following sentence is correct?

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Q285

The maximum likelihood method can be used to explore relationships among more diverse sequences, conditions that are not well handled by maximum parsimony methods.

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Q286

The standard error is defined as the square root of this computation.

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Q287

Bernoulli Nave Bayes Classifier is . . . . . . . .distribution

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Q288

How many terms are required for building a bayes model?

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Q289

Conditional probability is a measure of the probability of an event given that another event has already occurred.

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Q290

Problem:Players will play if weather is sunny. Is this statement is correct?

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Q291

Suppose we train a hard-margin linear SVM on n > 100 data points in R2, yielding a hyperplane with exactly 2 support vectors. If we add one more data point and retrain the classifier, what is the maximum possible number of support vectors for the new hyperplane (assuming the n + 1 points are linearly separable)?

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Q292

Which of the following can be true for selecting base learners for an ensemble?
1. Different learners can come from same algorithm with different hyper parameters
2. Different learners can come from different algorithms
3. Different learners can come from different training spaces

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Q293

Suppose you have fitted a complex regression model on a dataset. Now, you are using Ridge regression with tuning parameter lambda to reduce its complexity. Choose the option(s) below which describes relationship of bias and variance with lambda.

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Q294

In SVM, Kernel function is used to map a lower dimensional data into a higher dimensional data.

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Q295

You've just finished training a decision tree for spam classification, and it is getting abnormally bad performance on both your training and test sets. You know that your implementation has no bugs, so what could be causing the problem?

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Q296

Point out the wrong statement.

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Q297

. . . . . . . . which can accept a NumPy RandomState generator or an integer seed.

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Q298

. . . . . . . . adopts a dictionary-oriented approach, associating to each category label a progressive integer number.

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Q299

Which of the following properties are characteristic of decision trees?
1. High bias
2. High variance
3. Lack of smoothness of prediction surfaces
4. Unbounded parameter set

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Q300

What is back propagation?

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