g features (X_train), training labels (y_train), testing features (X_test) and testing labels (y_test)
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Hey guys can I get help with the following question:
Function 6
Write a function to return the number of false negatives (as an integer) of a logistic regression model
- Given the training features (X_train), training labels (y_train), testing features (X_test) and testing labels (y_test)
### START FUNCTION 6
def log_reg_fn(X_train, y_train, X_test, y_test):
# YOUR CODE HERE
### END FUNCTION 6
log_reg_fn(X_train_c, y_train_c, X_test_c, y_test_c)
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- Step 1. Intersection over Union # def intersection_over_union(dt_bbox, gt_bbox): ---> return iou Step 2. Evaluate Sample We now have to evaluate the predictions of the model. To do this, we will write a function that will do the following: Take model predictions and ground truth bounding boxes and labels as inputs. For each bounding box from the prediction, find the closest bounding box among the answers. For each found pair of bounding boxes, check whether the IoU is greater than a certain threshold iou_threshold. If the IoU exceeds the threshold, then we consider this answer as True Positive. Remove a matched bounding box from the evaluation. For each predicted bounding box, return the detection score and whether we were able to match it or not. def evaluate_sample(target_pred, target_true, iou_threshold=0.5): # ground truth gt_bboxes = target_true['boxes'].numpy() gt_labels = target_true['labels'].numpy() # predictions dt_bboxes =…sql function related question! Hi, I need to create a function that accepts officer_id and returns the keyword Active or Inactive. If officer_id exists in the system it finds the status of either A or I.(nested if) if the officer is active(a) then based on the last digit of badge number, if last digit is between 0-5 it returns 'ACTIVE ON DESK'. else if the last digit of badge number is greater than 5, it returns 'ACTIVE ON DUTY' If officer is inactive(I ), it returns Inactive. If officer_id does not exist, it returns 'not existing officer'Please help me with this!In Python, write a function that does least squares regression. The function should take input of an X and Y data. The output should be a dict in Python with the 1) best fit values for the intercept 2) the best-fit value for the slope, 3) the sum-squared error, 4) the residuals, and 5) the p-value for the two-sided hypthesis test of the slope being zero. Each component of the dict should be labeled. Test the function with simulated data.
- In Python, write a function that does least squares regression. The function should take input of an X and Y data set. The output should be a dict in Python with the 1) best fit values for the intercept 2) the best-fit value for the slope, 3) the sum-squared error, 4) the residuals, and 5) the p-value for the two-sided hypthesis test of the slope being zero. Each component of the dict should be labeled. Test the function with simulated data.Creating Functions Who's Return Shouldn't Be IgnoredThe Problem: Some functions return a value that never should be ignored. For example, there is no reason that anyone would want to call malloc and ignore the results. Is there any way to force people to use the return value of a function?Question 1: a)Population Growth The world population data spans from 1960 to 2017. We'd like to build a predictive model that can give us the best guess at what the population growth rate in a given year might be. We will calculate the population growth rate as follows:- Growth_rate=current_year_population−previous_year_populationprevious_year_population As such, we can only calculate the growth rate for the year 1961 onwards. Write a function that takes the population_df and a country_code as input and computes the population growth rate for a given country starting from the year 1961. This function must return a return a 2-d numpy array that contains the year and corresponding growth rate for the country. Function Specifications: Should take a population_df and country_code string as input and return a numpy array as output. The array should only have two columns containing the year and the population growth rate, in other words, it should have a shape (?, 2) where ? is…
- Question 3.1. Write a function called simulate_estimates. It should take 4 arguments: original_df : A DataFrame from which the data should be sampled, with 1 column named 'serial_number'. • sample_size: The size of each sample, an integer. (For example, to do resampling, we would pass the number of rows in original_df for this argument.) statistic: function that computes a statistic on a sample. This argument is the name of a function that takes a Series of serial numbers as its argument and returns a number (e.g. calculate_mean_based_estimate). repetitions: The number repetitions to perform (i.e. the number of resamples to create). It should simulate repetitions samples with replacement from the given DataFrame. For each of those samples, it should compute the statistic on that sample. Then it should return an array containing the value of that statistic for each sample (this means that the length of the returned array should be equal to repetitions). The code below provides an…4. Which function calls would provide the most helpful test of this function? Remember: With tests, you are attempting to figure out all the possible ways the function could be broken. function findMin(num1, num2){ if(num1 < num2){ return num1; } else { return num2; } } function findMin (num1 num2 if( numl < num2 ) return numl } else ( return num2 O A. findMin(-1, 0) findMin(2,4) findMin(5,10) Ов. findMin(5,3) findMin(7,2) findMin(5,1) O C. findMin(1,1) findMin(-2,2) findMin(0,3) O D. findMin(-1,1) findMin(1,-1) findMin(1,1)Please enumerate all of the situations when invoking inline functions will not get the expected results.
- Consider the following function shoots : def shoots(x: int) -> int: if x <= 0: return 0 4 elif x == 1: return shoots(x + 2) 6 elif x == 2: return shoots(x - 1) 80 elif x == 2: 9. return -1 10 else: 11 return shoots(x - 2) 2 3Implement the Function has_error Implement the function according to the specification. Use the test script testcurrency.py to aid your development before checking your answer below. CANNOT USE IF/CONDITIONAL STATEMENTS Instead, you should use what you know about boolean expressions def has_error(json):"""Returns True if the response to a currency query encountered an error. Given a JSON string provided by the web service, this function returns True if thequery failed and there is an error message. For example, if the json is '{"success":false,"src":"","dst":"","error":"Source currency code is invalid."}' then this function returns True (It does NOT return the error message'Source currency code is invalid'). On the other hand if the json is '{"success": true, "src": "2 United States Dollars", "dst": "1.772814 Euros", "error": ""}' then this function returns False. The web server does NOT specify the number of spaces after the colons. The JSON '{"success":true, "src":"2 United…Which of the following statements about functional-style programming is false? With functional-style programming capabilities you can write code that is more concise, clearer and easier to debug (find and correct errors). The min and max functions are examples of a functional-style programming concept called reduction. They reduce a collection of values to a single value. Other reductions you’ll see include the sum, average, variance and standard deviation of a collection of values. All reductions are built into Python—you cannot define custom reductions.