An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
13th Edition
ISBN: 9781461471370
Author: Gareth James
Publisher: SPRINGER NATURE CUSTOMER SERVICE
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Chapter 2, Problem 6E
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Difference between a parametric and non parametric model
| Parametric | Non parametric |
| It reduces estimating f to the problem of estimating parameters. | It avoids assumptions about the shape of f. |
| It uses flexible models. | It is excellent for non linear models. |
| The chosen model will not match the true unknown form. | It has the option to fit a wider range of possible shapes for f... |
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A) What is regression?
B) How we can use it to estimate relationship between dependent and independent variables?
C) How we can use it in machine learning?
what is regression and classification in machine learning?
Using specific examples, please explain the rationale behind your choice of one machine learning model over another.
Chapter 2 Solutions
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
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- What's the difference between logistic and linear regression? How do you avoid local minima in machine learning?arrow_forwardIn what ways are prescriptive models different from descriptive models? In what ways are prescriptive models different from predictive models? In what ways are descriptive models different from predictive models? What is a dependent variable? . What is an independent variable?arrow_forwardIs it feasible to differentiate between descriptive and prescriptive models by looking at the differences between the two?arrow_forward
- Can you explain your choice of model for machine learning using some examples?arrow_forwardModels for machine learning are often taught using large, well-characterized data sets (or attributes). However, we are cognizant of the fact that characteristics may be meaningful or irrelevant depending on the context. Give some examples of how the "utility" of a feature may be explained.arrow_forwardIs it feasible to differentiate between a prescriptive model and a descriptive model by analyzing the ways in which they vary from one another?arrow_forward
- Can the distinction between a descriptive model and a prescriptive model be made by examining their differences?arrow_forwardCould you perhaps supply some examples to support your choice of machine learning model?arrow_forwardShow the differences between machine learning models and deep learning models in terms of the length of training time that is needed, the quantity of data and processing power that is necessary, the accuracy requirements, the hyperparameter adjustment, and the hardware dependencies.arrow_forward
- What is the primary objective of linear regression in machine learning? A) Maximizing accuracy of predictions.B) Minimizing the number of features.C) Minimizing the sum of squared differences between predicted and actual values. D) Maximizing the correlation coefficient between variables.arrow_forwardIs it possible to train machine learning models using log data?arrow_forwardWhat is an example of the differences in using precision and recall compared to the confusion matrix for gauging the performance of a machine learning model algorithmarrow_forward
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