Answer:
Check the explanation
Explanation:
Lasso: R example
To run Lasso Regression you can re-use the glmnet() function, but with the alpha parameter set to 1.
# Perform 10-fold cross-validation to select lambda --------------------------- lambdas_to_try <- 10^seq(-3, 5, length.out = 100) # Setting alpha = 1 implements lasso regression lasso_cv <- cv.glmnet(X, y, alpha = 1, lambda = lambdas_to_try, standardize = TRUE, nfolds = 10) # Plot cross-validation results plot(lasso_cv)
Best cross-validated lambda lambda_cv <- lasso_cv$lambda.min # Fit final model, get its sum of squared residuals and multiple R-squared model_cv <- glmnet(X, y, alpha = 1, lambda = lambda_cv, standardize = TRUE) y_hat_cv <- predict(model_cv, X) ssr_cv <- t(y - y_hat_cv) %*% (y - y_hat_cv) rsq_lasso_cv <- cor(y, y_hat_cv)^2 # See how increasing lambda shrinks the coefficients -------------------------- # Each line shows coefficients for one variables, for different lambdas. # The higher the lambda, the more the coefficients are shrinked towards zero. res <- glmnet(X, y, alpha = 1, lambda = lambdas_to_try, standardize = FALSE) plot(res, xvar = "lambda") legend("bottomright", lwd = 1, col = 1:6, legend = colnames(X), cex = .7)
Kindly check the Image below.
These principles are not explicit to one kind of program and are increasingly broad "best practice" rules that assist designers with composing code that is easier to maintain.
<u>Explanation:</u>
A set of programming guidelines that are executed to play out a particular undertaking according to the prerequisites of the client is known as programming. Every product has some essential standards to follow. In light of all product frameworks have basic quality traits, including accessibility, modifiability, execution, security and wellbeing, testability and ease of use, the key programming thoughts give basic arrangements or strategies to help those characteristics.
It is generally less expensive, over the long haul, to utilize programming designing strategies and methods for programming frameworks instead of simply compose the projects as though it was an individual programming venture.
Answer:
See explaination
Explanation:
The reasons why indexed sequential search structure is better are:
1. In index sequential search any field of the records can be used as the key. This key field can be numerical or alphanumerical.
2. Since each record has its data block address, searching for a record in larger database is easy and quick. There is no extra effort to search records. But proper primary key has to be selected to make efficient.
3. This method gives flexibility of using any column as key field and index will be generated based on that. In addition to the primary key and its index, we can have index generated for other fields too. Hence searching becomes more efficient, if there is search based on columns other than primary key.
The reasons why 5 B-tree is better:
1.The B-tree Provides support for range of queries in an efficient manner and You can iterate over an ordered list of elements.
2. B-Tree algorithms are good for accessing pages (or blocks) of stored information which are then copied into main memory for processing. In the worst case, they are designed to do dynamic set operations in O(lg n) time because of their high "branching factor" (think hundreds or thousands of keys off of any node). It is this branching factor that makes B-Trees so efficient for block storage/retrieval, since a large branching factor greatly reduces the height of the tree and thus the number of disk accesses needed to find any key.
3. It is a generalization of a BST in that a node can have more than two children. These are self-balancing and hence the average and worst complexities is logarithmic. We opt for these when the data is too huge to fit in main memory. These structures are used in database indexing and help in faster operations on disk
the additional informations is we should first decide to choose which structure is suiatable for which algoritm in terms of space and time and then use the appropriate search algorithm.
Select the
comments feature.
We use comments in our documents to track issues for follow
up or make suggestions to other people. A comment is inserted inside a balloon or
a box that appears in the document's margins. Whatever the situation you may be in,
you can easily add comments in a word document.
Answer:
I guess c no. is the answer
