Question

Answer the following questions 3. (a) Consider the contingency table below and compute the ACCURACY rate and ERROR rate for m

1 0
Add a comment Improve this question Transcribed image text
Answer #1

3).

a) From the given model M1,we have

Total = n = (70+10+10+10) = 100, True negative (TN) = 70 , True positive (TP) = 10 , False negative (FN) = 10 , False positive (FP) = 10

So, Accuracy = (TP+TN)/n = (10+70)/100 = 0.8,

Error Rate = (FP+FN)/n = (10+10)/100 = 0.2

b) From the given model M2, we have

Total = n = 70+0+20+10 = 100 , TN = 70 ,TP = 10, FN = 20 , FP = 0. So,

Accuracy = (TP + TN)/n = (10+70)/100 = 0.8,

Error Rate = (FP + FN)/n = (0+20)/100 = 0.2.

c) Cost for model M1 = 70(-1) + 10(100) + 10(1) +10(0)

= ( -70+1000+10+0) = 940

Cost for model M2 = 70(-1) + 0(100) + 20(1) + 10(0)

= (-70+0+20+0) = (-50).

Add a comment
Know the answer?
Add Answer to:
Answer the following questions 3. (a) Consider the contingency table below and compute the ACCURACY rate...
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions
  • Answer the following questions 3. (a) Consider the contingency table below and compute the ACCURACY rate...

    Answer the following questions 3. (a) Consider the contingency table below and compute the ACCURACY rate and ERROR rate for model M1. MODEL M1 PREDICTED CLASS Class-Yes Class No ACTUAL Class Yes 10 70 CLASS Class No 10 10 (b) Consider the contingency table below and compute the ACCURACY rate and ERROR rate for model M2 MODEL M2 PREDICTED CLASS Class Yes Class-No ACTUAL Class-Yes 70 CLASS Class No 10 20 (c) Given the following cost matrix, compute the cost...

  • Confusion Matrix The following table summarize performance of a classification algorithm for identifying cancerous (Malignant) cells....

    Confusion Matrix The following table summarize performance of a classification algorithm for identifying cancerous (Malignant) cells. Table-1: Outcome from a classifier Model M1 Prediction Benign Malignant Actual Benign 60 15 Malignant 5 35 Compute the accuracy and error rate of the classifier. Compute the sensitivity and specificity of the classifier. Compute the precision and recall of the classifier. Compute the F1 measure of the classifier. Compute the Fβ measure of the classifier in which weights recall twice as much as...

  • 6. Calculate the following performance metrics for the confusion matrix shown below. * True positive rate....

    6. Calculate the following performance metrics for the confusion matrix shown below. * True positive rate. * True negative rate. + False positive rate. + False negative rate. + Precision. + Accuracy + Error rate. Actual class Positive Negative Positive 30 15 Predicted Class Negative 10 85

  • Question 1 2 pts Sensitivity and Specificity are plotted on an ROC Curve. True False Question...

    Question 1 2 pts Sensitivity and Specificity are plotted on an ROC Curve. True False Question 2 2 pts To obtain an honest estimate of future classification error, we use the classification matrix that is computed from validation data test data training data Question 3 2 pts The classification matrix, also called confusion matrix, gives estimates of the true classification and misclassification rates. True False Question 4 8 pts A data mining routine has been applied to a transaction dataset...

  • Q4) After we ran a model, we got the following results as presented in the confusion...

    Q4) After we ran a model, we got the following results as presented in the confusion Prediction Actual Class Yes No Yes 1100 70 No 130 700 based on this output the following questions: 1. What is the value of classification accuracy?|| 2. How many instances are incorrectly classified? 3. How many instances were assigned true negative? 4. How many instances were assigned true positive?

  • Evaluating Predictive Performance ( Business Analytics) Confusion Matrix !!! A publisher plans to boost the sales...

    Evaluating Predictive Performance ( Business Analytics) Confusion Matrix !!! A publisher plans to boost the sales of its most popular magazine by sending out promotional mails. We refer to a customer as a responder if he/she subscribes to the magazine for the next year after receiving a promotional mail. Otherwise the customer is referred to as a non-responder. Denote responder by C1 and non-responder by C2. The publisher has built a model to classify each customer as either a responder...

  • C) Estimate the linear model for a state's unemployment rate shown below (i.e. estimate Bo and β1...

    Only question 6 please, this is the model referred to in Question 6 from 5.c c) Estimate the linear model for a state's unemployment rate shown below (i.e. estimate Bo and β1) using OLS. Write the resulting regression equation. unemployment rate-β0 + β|minimum wage + ε 6. The following questions ask you to use the regression model you estimated to predict unemployment rates (ie, the model in 5.c). Use the unemployment and minimum wage data from the table above to...

  • Consider the training examples shown in the table below for a binary classification problem. (a) What...

    Consider the training examples shown in the table below for a binary classification problem. (a) What is the entropy of this collection of training examples with respect to the positive class? (b) What are the information gains of a1 and a2 relative to these training examples? (c) For a3, which is a continuous attribute, compute the information gain for every possible split. (d) What is the best split (among a1 a2, and a3) according to the information gain? (e) What...

  • Refer to Table 1 and Table 2 below to answer questions 46 through 50. Assume that...

    Refer to Table 1 and Table 2 below to answer questions 46 through 50. Assume that the supply of money (MⓇ) and the demand for money (Md) in an economy are described by Table 1 (note that money is defined as M1). Assume that the amount of business investment (1) is described by Table 2. Also assume that the banking system is always loaned up and there is no crowding out. Table 1 Table 2 Md - r M r...

  • 3. Consider a labeled data set containing 100 data instances which are randomly partitioned into two...

    3. Consider a labeled data set containing 100 data instances which are randomly partitioned into two sets A and B, each containing 50 instances. We use A as the training set to learn two decision trees T10 with 10 leaf nodes and T100 with 100 leaf nodes. The accuracies of the two decision trees on data sets A and B are shown below: Data Set T100 А. T10 0.86 0.84 B 0.97 0.77 (a) Based on the accuracies shown in...

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT