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Mice21 [21]
3 years ago
7

Write at least and explain four types of escape sequences and create an example in an IDE which consist of the mentioned escape

sequences.
Computers and Technology
1 answer:
slamgirl [31]3 years ago
5 0

Answer:

- \' is used to escape a single quote in a string enclosed in single quotes like;

my_string = 'this is John\'s ball'.

- \n is used to jump to a new line, Eg;

my_string = "Johns is a good boy\nbut he hates going to school."

the next set of the string after the '\n' character is displayed on the next line.

- \t is used to add a tab space to a string.

my_string = 'Jane is \thungry'

the character adds four character spaces before the word 'hungry'.

- \r adds a carriage return (or enter in keyboards) to start a new block paragraph in a string.

my_string = "Johns is a good boy\rbut he hates going to school."

Explanation:

Escape sequences in programming are used to format strings or output syntax of a program. They always begin with the backslash. Examples of escape sequence are " \' ", "\n", "\t", "\r", etc.

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Arisa [49]

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.

5 0
2 years ago
When researching Information about technology for use in a project, it is NOT important to consider the date that the informatio
REY [17]

Answer:

B. False

Explanation:

Hope this helps!

4 0
1 year ago
To estimate the percentage of defects in a recent manufacturing​ batch, a quality control manager at Sony selects every 14th mus
sukhopar [10]

Answer:C. Systematic Sampling

Explanation:

Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size.

Systematic sampling involves selecting items from an ordered population using a skip or sampling interval. The use of systematic sampling is more appropriate compared to simple random sampling when a project's budget is tight and requires simplicity in execution and understanding the results of a study.

8 0
3 years ago
Characteristics of a cohesive group include all of the following EXCEPT: a. ​support b. a lack of bonding c. mutuality within th
Brilliant_brown [7]

Answer:

Option B i.e., a lack of bonding is the correct answer.

Explanation:

Cohesion is defined as the ability to work in a group, so many time the following situation or problems that are lack of bonding occurs between the mates or the group members because while they achieving their goals there is the understanding problem may occur between them or sometime their ideas should be a mismatch.

4 0
3 years ago
CO! Oher...9
kondor19780726 [428]

Answer:

Altitude of the town(h1) = 1,196.8 m

Explanation:

Given:

Height of barometer(h) = 65 cm Hg = 0.65

Standard atmospheric pressure  = 76 cm Hg = 0.76

Density of mercury(Pm) = 13,600 kg/m³

Density of  air (Pa) = 1.25 kg/m³

Find:

Altitude of the town(h1)

Computation:

Pressure due column = Δp mercury column

(Pa)(h1) = (Pm)(h)

(1.25)(h1) = (13,600)(0.76-0.65)

(1.25)(h1) = 1,496

Altitude of the town(h1) = 1,196.8 m

6 0
3 years ago
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