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We have been given a dataset with n records in which we have input attribute as x and output attribute as y. Suppose we use a linear regression method to model this data. To test our linear regressor, we split the data in training set and test set randomly. Now we increase the training set size gradually. As the training set size increases, what do you expect will happen with the mean training error?

We have been given a dataset with n records in which we have input attribute as x and output attribute as y. Suppose we use a linear regression method to model this data. To test our linear regressor, we split the data in training set and test set randomly. Now we increase the training set size gradually. As the training set size increases, what do you expect will happen with the mean training error? Correct Answer can't say

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We have been given a dataset with n records in which we have input attribute as x and output attribute as y. Suppose we use a linear regression method to model this data. To test our linear regressor, we split the data in training set and test set randomly. What do you expect will happen with bias and variance as you increase the size of training data?
What is/are true about ridge regression?
1. When lambda is 0, model works like linear regression model
2. When lambda is 0, model doesn't work like linear regression model
3. When lambda goes to infinity, we get very, very small coefficients approaching
04. When lambda goes to infinity, we get very, very large coefficients approaching infinity.
Suppose you have fitted a complex regression model on a dataset. Now, you are using Ridge regression with tuning parameter lambda to reduce its complexity. Choose the option(s) below which describes relationship of bias and variance with lambda.
Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of it's hyper parameter.What would happen when you use very large value of C(C->infinity)?
Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of it's hyper parameter.What would happen when you use very small C (C~0)?
In the following question, the first and the last part of the sentence/passage are numbered 1 and 6. The rest of the sentence/passage is split into four parts and named P, Q, R, S. These four parts are not given in their proper order. Read the sentence/passage and find out which of the four combinations is correct. S1. We go to schools, colleges, universities to complete our education and start earning our livelihood.  P. We take up jobs, practice professions, or start our own businesses so that we can earn money to make our living. Q. But which of these institutions make us capable of managing our own hard-earned money?—probably a very few of them. R. Financial literacy is knowing the basic financial management principles and applying them in our day-to-day life. S. As human beings, we are not expected to know the nitty-gritty of financial management.  S6. But managing our own money in a way that does not negatively affect us and our family is important.
In the question one statement is given, followed by two conclusions, I and II. You have to consider the statement to be true even if it seems to be at variance from commonly known facts. You have to decide which of the given conclusions, if any, follows from the given statement. Statement: A function is a relation between a set of input elements and a set of possible output elements where each input is related to exactly one output. Conclusion I: Every input element is related to every output element. Conclusion II: Every input element is related to one element of the output.
Read the passage carefully and choose the best answer to each question out of the four alternatives and click the button corresponding to it. It's nothing short of a revolution in how we eat, and it's getting closer every day. Yes, a lot of people are obese, and yes, the definition of "healthy eating" seems to change all the time. But in labs and research centres around the world, scientists are racing to match our genes and our taste buds, creating the perfect diet for each of us, a diet that will fight disease, increase longevity, boost physical and mental performance, and taste great to boot. As food scientist J.Bruce German says, "The foods we like the most will be the most healthy for us." Is that going to be a great day, or what? All this will come to pass, thanks to genomics, the science that maps and describes an individual's genetic code. In the future, personalized DNA chips will allow us to assess our own inherited predispositions for certain diseases, then adjust our diets accordingly. So, if you're at risk for heart disease, you won't just go on a generic low-fat diet. You'll eat foods with just the right amount and type of fat that's best for you. You'll even be able to track your metabolism day-to-day to determine what foods you should eat at any given time, for any given activity. "Since people differ in their genetics and metabolism, one diet won't fit all," says German. As complex as all this sounds, it could turn out to be relatively simple. What are scientists doing?
Read the passage carefully and choose the best answer to each question out of the four alternatives and click the button corresponding to it. It's nothing short of a revolution in how we eat, and it's getting closer every day. Yes, a lot of people are obese, and yes, the definition of "healthy eating" seems to change all the time. But in labs and research centres around the world, scientists are racing to match our genes and our taste buds, creating the perfect diet for each of us, a diet that will fight disease, increase longevity, boost physical and mental performance, and taste great to boot. As food scientist J.Bruce German says, "The foods we like the most will be the most healthy for us." Is that going to be a great day, or what? All this will come to pass, thanks to genomics, the science that maps and describes an individual's genetic code. In the future, personalized DNA chips will allow us to assess our own inherited predispositions for certain diseases, then adjust our diets accordingly. So, if you're at risk for heart disease, you won't just go on a generic low-fat diet. You'll eat foods with just the right amount and type of fat that's best for you. You'll even be able to track your metabolism day-to-day to determine what foods you should eat at any given time, for any given activity. "Since people differ in their genetics and metabolism, one diet won't fit all," says German. As complex as all this sounds, it could turn out to be relatively simple. What does J. Bruce German say?
Read the passage carefully and choose the best answer to each question out of the four alternatives and click the button corresponding to it. It's nothing short of a revolution in how we eat, and it's getting closer every day. Yes, a lot of people are obese, and yes, the definition of "healthy eating" seems to change all the time. But in labs and research centres around the world, scientists are racing to match our genes and our taste buds, creating the perfect diet for each of us, a diet that will fight disease, increase longevity, boost physical and mental performance, and taste great to boot. As food scientist J.Bruce German says, "The foods we like the most will be the most healthy for us." Is that going to be a great day, or what? All this will come to pass, thanks to genomics, the science that maps and describes an individual's genetic code. In the future, personalized DNA chips will allow us to assess our own inherited predispositions for certain diseases, then adjust our diets accordingly. So, if you're at risk for heart disease, you won't just go on a generic low-fat diet. You'll eat foods with just the right amount and type of fat that's best for you. You'll even be able to track your metabolism day-to-day to determine what foods you should eat at any given time, for any given activity. "Since people differ in their genetics and metabolism, one diet won't fit all," says German. As complex as all this sounds, it could turn out to be relatively simple. What is genomics?