Question

Based on classification and regression models what is the optimal model to predict wine quality.

Based on classification and regression models what is the optimal model to predict wine quality.
Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

Classification and regression model is very much useful to predict the future values of the dependent variable based on the independent variables.

When we take quality of the wine as a dependent variable, independent variables would be Cost of the wine, sunlight, quality of fruits etc

In order to reach the optimal solution or optimal prediction, we make sure that the Residual error must be as low as possible. Residual error or Error is the "Sum of the squares of the difference between observed value and expected value"

Error may be positive or negative or zero. This concept of Residual error was proposed by Legrang.

Thank you

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
In an attempt to develop a model of wine quality as judged by wine​ experts, data...
In an attempt to develop a model of wine quality as judged by wine​ experts, data on alcohol content and wine quality was collected from variants of a particular wine. From a sample of 21​wines, a model was created using the percentages of alcohol to predict wine quality. From the results of that​ regression, b1 = 0.3607 and Sb1 = 0.1879 a. At the 0.05 level of​ significance, is there evidence of a linear relationship between the percentage of alcohol...
Explain the following models and why they are used for data analysis - regression model -...
Explain the following models and why they are used for data analysis - regression model - classification model - decision tree model
Prompt 1: A decision tree is used for both classification and regression. Sometimes, to improve classification...
Prompt 1: A decision tree is used for both classification and regression. Sometimes, to improve classification accuracy and avoid overfitting, a combination of decision tree models can be used instead of a single decision tree model. Prompt 2: The concept of using several decision tree models for a classification or regression task is known as random forest. In at least two paragraphs, explain in your own words how random forest works.
Predictive modeling uses statistics to predict outcomes through the use of models such as one of...
Predictive modeling uses statistics to predict outcomes through the use of models such as one of below: Naive Bayes k-nearest neighbor algorithm Majority classifier Support vector machines Random forests Boosted trees Classification and Regression Trees (CART) Multivariate adaptive regression splines (MARS) Neural Networks Ordinary Least Squares Generalized Linear Models (GLM) Logistic regression Generalized additive models Robust regression Semiparametric regression Choose one model to research further and then create a specific example/prototype of how it could be applied to a real-world...
Based on a sample of 30 observations the population regression model to predict salary of employees...
Based on a sample of 30 observations the population regression model to predict salary of employees (dependent variable, numerical continuous) based on independent variables: education, measured as number of years of education (numerical, discrete but so many values), work experience, measured as number of years of work experience (numerical, continuous, for example 3.5 means 3 years 6 month work experience) department, department of the employee, There are three main departments in the organization (categorical nominal) Assume it affects only intercept...
Which one of the below is false? Group of answer choices In regression models, if p-value...
Which one of the below is false? Group of answer choices In regression models, if p-value for a predictor is greater than alpha, then that predictor is helpful to predict the response variable. High correlation correficents indicate strong relationship between the variables of a regression model. In regression models, we use p-values and alpha to determine if the model is significant Higher coefficient of determination values are desired in regression models.
Is the following example of classification, regression, or clustering problems? Why? An online business wants to...
Is the following example of classification, regression, or clustering problems? Why? An online business wants to build a model to predict future sales revenue of their customers. They collect information from existing customers: what browser they are using, what state they are from, and what products they have purchased in the past.
A multiple linear regression model based on a sample of 17 weeks is developed to predict...
A multiple linear regression model based on a sample of 17 weeks is developed to predict standby hours based on the total staff present and remote hours. The SSR is 20,905.02 and the SSE is 25,434.29. (use 0.05 level of significance) H0​: B1 = B2 = 0 H1​: At least one Bj does not equal 0, j = 1, 2 1. Calculate the test statistic. Fstat= _____ 2. Find the p-value. p-value= _____ 3. Compute the coefficient of multiple​ determination,...
A multiple linear regression model based on a sample of 24 weeks is developed to predict...
A multiple linear regression model based on a sample of 24 weeks is developed to predict standby hours based on the total staff present and remote hours. The SSR is 31,193.47 and the SSE is 33,923.99. complete parts a through d. a. Determine whether there is a significant relationship between standby hours and the two independent variables at the .05 level of significance. test statistic pvalue state the conclusion b. Interpret the meaning of the p-value. c. compute the coefficent...
Using the BP data set, produce regression models for BP with Independent Variables as follows: ?...
Using the BP data set, produce regression models for BP with Independent Variables as follows: ? Age Only ? Weight Only ? Weight and Age Comment on the quality of each of these models as a predictor of BP based on the Coefficient of Correlation (r2 ) Use your Weight and Age Model to retroactively predict BP for the data pairs given, compare them against the actual BP Data and calculate the MSE. Use the Weight Model to retroactively predict...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT