Recent questions tagged cross-validation

1 1 vote
2 2 answers
665
665 views
Consider that you are training a classifier for a $10$ -class classification problem. Each input is represented as a $512$ -dimensional vector. There are $1000$ samples, ...
1 1 vote
1 1 answer
320
320 views
Given computational budget of 100 model training runs, compare: (A) 10-fold CV repeated 10 times vs (B) 20-fold CV repeated 5 times. Which has better bias-variance tradeo...
0 0 votes
1 1 answer
382
382 views
Consider a dataset with 1000 samples. You perform 10-fold cross-validation with a neural network. If training takes 2 minutes per fold, and the model achieves 95% accurac...
0 0 votes
0 0 answers
271
271 views
Consider a scenario where we use leave-one-out cross-validation (LOOCV) with Support Vector Machines (SVM) for binary classification. Given a dataset $\mathcal{D}=$ $\lef...
1 1 vote
2 2 answers
517
517 views
Given the 2D dataset, which of the following is true regarding the performance of 1-nearest neighbor (1-NN) and Support Vector Machines (SVM) in terms of leave-one-out cr...
0 0 votes
0 0 answers
154
154 views
Given the 2D dataset, which of the following is true regarding the performance of 1-nearest neighbor (1-NN) and Support Vector Machines (SVM) in terms of leave-one-out cr...
0 0 votes
1 1 answer
206
206 views
$\text { Suppose you have this data set with one real-valued input and one real-valued output. }$I.What is the mean squared leave one out cross validation error of using ...
0 0 votes
1 1 answer
181
181 views
Mark all the statements that are true, about cross-validation.A.Increasing k in k -fold cross validation decreases the bias of the model.B.We use cross validation because...
0 0 votes
0 0 answers
127
127 views
Consider the following dataset with one real-valued input $x$ and one binary output $y$. We are going to use $k$-NN with unweighted Euclidean distance to predict $y$ for ...
1 1 vote
1 1 answer
202
202 views
Which of the following statement is correct $?$$(I)$ The test set is divided into $k$ folds. For each fold of the test set, we use the entire training set to train the mo...
0 0 votes
0 0 answers
130
130 views
Suppose we have a training dataset of 90 points, and a test set of 30 points, and want to know which $\lambda$ value is best for a ridge regression model. Our candidate h...
0 0 votes
0 0 answers
116
116 views
Suppose we have a training dataset of 90 points, and a test set of 30 points, and want to know which $\lambda$ value is best for a ridge regression model. Our candidate h...
0 0 votes
1 1 answer
137
137 views
Suppose you are using a Majority Classifier on the following training set containing 10 examples where each example has one real-valued feature, $x$, and a binary class l...
0 0 votes
0 0 answers
124
124 views
Suppose you are using a Majority Classifier on the following training set containing 10 examples where each example has one real-valued feature, $x$, and a binary class l...
0 0 votes
0 0 answers
115
115 views
Under which of the following conditions is $\boldsymbol{k}$-fold cross-validation the same as leave-one-out cross-validation ?A. The training set and test set have the sa...
0 0 votes
0 0 answers
111
111 views
.Suppose you have picked the parameter $\theta$ for a model using 10 -fold cross validation. The best way to pick a final model to use and estimate its error is to A .pic...
0 0 votes
0 0 answers
154
154 views
Which of the following statement(s) is(are) true for k-NN ?A. k represents the number of classes.B. The final outcome of the algorithm may change with the distance measur...
1 1 vote
1 1 answer
135
135 views
You are training a soft-margin SVM on a binary classification problem. You find that your model's training accuracy is very high, while your validation accuracy is very l...
0 0 votes
0 0 answers
118
118 views
Why is it important to use a different test set to evaluate the final performance of the model, rather than the validation set used during model selection?A. The model ma...
0 0 votes
0 0 answers
98
98 views
Aman and Ed built a model on their data with two regularization hyperparameters $\lambda$ and $\gamma$. They have 4 good candidate values for $\lambda$ and 3 possible val...
0 0 votes
0 0 answers
177
177 views
Consider a nearest neighbor classifier that chooses the label for a test point to be the label of its nearest neighboring training example. What is its leave-oneout cross...
0 0 votes
0 0 answers
108
108 views
Suppose we have a design matrix $\mathbb{X}$ comprising of $n$ observations, $d$ features, and an additional intercept term. We decide to use $\mathbb{X}$ to create, tune...
0 0 votes
0 0 answers
102
102 views
Random forest is created from a number of decision trees, with each decision tree created from a bootstrapped version of the original training set. One hyperparameter of ...
0 0 votes
0 0 answers
94
94 views
Leave-one-out cross-validation (LOOCV) is a special case of k -fold cross-validation where:The training set contains all but one sample, and the remaining sample is used ...
0 0 votes
0 0 answers
118
118 views
Assume we have a data matrix $X$. Which of the following is a true statement when comparing leave-one-out cross validation (LOOCV) error with the true error? LOOCV error ...
0 0 votes
0 0 answers
121
121 views
$k$-fold cross-validation with $k=100$ is computationally more expensive (slower) than "leave-one-out" cross validation. (Assume that there are enough data points to divi...
1 1 vote
0 0 answers
177
177 views
Suppose we use leave-one-out cross validation meaning we use 7 -fold cross validation with a split of 6 to 1 between training set and validating set. Compute the average ...
0 0 votes
0 0 answers
139
139 views
Suppose we have $m$ data points in our training set and $n$ data points in our test set. In leave-one-out cross validation, we only use one data point for validation whil...