Infosys Certified Machine Learning Professional
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Real Lex exam-pattern multiple-choice questions for the Infosys Certified Machine Learning Professional certification. Each question includes the correct answer. The full question bank is available to Premium members.
- Question 1
ROC (Receiver Operating Characteristics) curve is defined as
- ✓
Plot of FPR vs Precision
Correct - B
Plot TPR vs FPR
- C
Both of the above
- D
None of the above
- ✓
- Question 2
How do we define True Positive Rate (TPR) or Recall or Sensitivity?
- ✓
TP / (TP + FN)
Correct - B
TP / (TP + FP)
- C
1 - (TN / (TN + FP))
- D
None of the above
- ✓
- Question 3
What should we do to remove multi collinearity among variables
- ✓
Check VIF
Correct - B
Check P-Value
- C
Check R Square
- D
Check Adjusted R Square
- ✓
- Question 4
Given 1000 records, 1000 models are trained with 999 records as part of training sample and remaining 1 sample for testing, and the error rate is averaged out, this validation technique can be called as
- ✓
Hold-out
Correct - B
K-fold cross-validation
- C
LOOCV (leave one out cross validation)
- D
Bootstrapping
- ✓
- Question 5
Which Statement is TRUE from the following
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In Forward Selection procedure , the first independent variable will be included in the equation which has the highest correlation with the response variable and with the significance p value closest to 0
Correct - B
In Backward Elimination procedure the first independent variable to be excluded will be the one with the smallest contribution to the reduction of error of sum of squares
- C
In Stepwise Selection procedure the predictor variable that enters in the earlier stages of selection may be eliminated in the later stage, depending on significance level changes of T-Test values when every predictor variable is added
- D
All the options
- ✓
- Question 6
Consider a regression line y=ax+b, where a is the slope and b is the intercept. If we know the value of the slope then by using which option can we always find the value of the intercept?
- ✓
Put the value (0,0) in the regression line
Correct - B
Put any value from the points used to fit the regression line and compute the value of b
- C
Put the mean values of x & y in the equation along with the value "a" to get "b"
- D
None of the above can be used
- ✓
- Question 7
Choose the correct option with respect to the Linear Regression model.
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Greater the SSE for the model, the better fit, is the model
Correct - B
Linear model cannot be used when data is more than 2-dimensional
- C
Though the sum of prediction errors may be zero, SSE may not be zero
- D
If the sum of prediction errors is zero, SSE is also zero
- ✓
- Question 8
What is meant by Adjusted R-Squared Value?
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R-squared value adjusted as per the distribution of data
Correct - B
R-squared value adjusted for number of predictors in the model
- C
R-squared value adjusted by cross validating the model
- D
R-squared value adjusted for missing value in the data
- ✓
- Question 9
What is the minimum value of Variance Inflation Factor (VIF) in a linear regression model?
- ✓
0.0
Correct - B
0.5
- C
0.6932
- D
1.0
- ✓
- Question 10
A multiple linear regression model gives a very low RMSE on train data but a high RMSE on test data. What is the likely issue?
- ✓
It is an under fitted model
Correct - B
The model is very well generalized
- C
It is an overfitted model
- ✓
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