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What is the Learning Technique in which the right answer is given for each example in the data called ?
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What is the Learning Technique in which the right answer is given for each example in the data...
asked
May 29, 2019
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Machine Learning
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param1987
What is the Learning Technique in which the right answer is given for each example in the data called ?
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answered
May 29, 2019
by
rajeshsharma
Supervised Learning
Technique in which the right answer is given for each example in the data called
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What is the process of subtracting the mean of each variable from its variable called ?
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May 29, 2019
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What is the process of dividing each feature by its range called ?
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May 29, 2019
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What is the name of the function that takes the input and maps it to the output variable called ?
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May 29, 2019
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Machine Learning
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param1987
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Cost function in linear regression is also called squared error function.
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May 29, 2019
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Machine Learning
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param1987
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Problems that predict real values outputs are called ?
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May 29, 2019
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Machine Learning
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param1987
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For different parameters of the hypothesis function we get the same hypothesis function.
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May 29, 2019
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Machine Learning
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param1987
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The objective function for linear regression is also known as Cost Function.
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May 29, 2019
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Machine Learning
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param1987
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The result of scaling is a variable in the range of [1 , 10].
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May 29, 2019
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Machine Learning
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param1987
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How are the parameters updates during Gradient Descent Process ?
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May 29, 2019
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param1987
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____________ controls the magnitude of a step taken during Gradient Descent .
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May 29, 2019
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Machine Learning
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param1987
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Output variables are known as Feature Variables .
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May 29, 2019
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Machine Learning
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param1987
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Input variables are also known as feature variables.
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May 29, 2019
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What is the Learning Technique in which the right answer is given for each example in the data called?
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Apr 14, 2021
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ML Exploring the Model
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SakshiSharma
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There is no exact formula for calculating the number of hidden layers, as well as the number of neurons in each hidden layer.
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What are the three stages for creating a model in machine learning?
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Imagine, you are given a dataset consisting of variables having more than 30% missing values.
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Nov 28, 2019
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