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

Related MCQs

•          which can accept a NumPy RandomState generator or an integer seed.
•           which can accept a NumPy RandomState generator or an integer seed.
•           which can accept a NumPy RandomState generator or an integer seed.
• In which of the following each categorical label is first turned into a positive integer and then transformed into a vector where only one feature is 1 while all the others are 0.
•              adopts a dictionary-oriented approach, associating to each category label a progressive integer number.
• _______adopts a dictionary-oriented approach, associating to each category label a progressive integer number.
• 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
• Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results.
• What is true about K-Mean Clustering? 1. K-means is extremely sensitive to cluster center initializations 2. Bad initialization can lead to Poor convergence speed 3. Bad initialization can lead to bad overall clustering
• What is true about an ensembled classifier? 1. Classifiers that are more “sure” can vote with more conviction 2. Classifiers can be more “sure” about a particular part of the space 3. Most of the times, it performs better than a single classifier