Python regression b) When adding more variables to a linear model, what is true about the R-squared value?
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Python
regression
b)
When adding more variables to a linear model, what is true about the R-squared value?
c)
Adding more variables always leads to a lower test MSE.
False
True
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- Python question please include all steps and screenshot of code. Also please provide a docstring, and comments throughout the code, and test the given examples below. Thanks. Implement function heads() that takes no input and simulates a sequence of coin flips.The simulation should continue as long as 'HEAD' is flipped. When the outcome of a flipis 'TAIL', the function should return the number of 'HEAD' flips made up to that point.For example, if the simulation results in outcomes 'HEAD', 'HEAD', 'HEAD', 'TAIL', thefunction should return 3. NOTE: Recall that random.choice(['HEAD', 'TAIL']) returns'HEAD' or 'TAIL' with equal probability.>>> heads()0 # TAIL is the outcome of the first coin flip>>> heads()2 # The coin flips were HEAD, HEAD, TAIL>>> heads()1 # The coin flips were HEAD, TAIL>>> heads()5 # The coin flips were HEAD, HEAD, HEAD, HEAD, HEAD, TAILPlease help me with this in c++. A simulation creates a model of a real-world situation, allowing us to introduce a variety of conditions and observe their effects. For instance, a flight simulator challenges a pilot to respond to varying conditions and measures how well the pilot responds. Simulation is frequently used to measure current business practices, such as the number of checkout lines in a grocery store or the number of tellers in a bank, so that management can determine the fewest number of employees required to meet customer needs. Airlines have been experimenting with different boarding procedures to shorten the entire boarding time, keep the flights on-time, reduce aisle congestion, and make the experience more pleasant for passengers and crew. A late-departing flight can cause a domino effect: the departure gate is tied up and cannot be used by other landing or departing flights, passengers on board the late flight may miss connecting flights and require rebooking and…True/False 8. A developer should use either top-down or spiral design, but not both.
- python please help no other answers have been right :(Binning methods sorted data value by consulting its “neighbor- hood,” that is, the values around it. Apply also the equal distance binning method in the sorted values The sorted values are distributed into a number of “buckets,” or bins. Price = 4, 8, 15, 21, 21, 24, 25, 28, 34, 36, 40, 50 In smoothing by bin means, each value in a bin is replaced by the mean value of the bin. Smoothing by bin means: Bin a: Bin b: Bin c:Models are used for a variety of purposes. Sort the models into groups.
- PYTHON In order to parse data to start a simulation, users must enter data correctly. Suppose that the simulation requires 2 information from the user, which is called 'soil_key' and 'soil_data.' The user will enter 'soil_key' first, following with 'soil_data.' We need to check if the user enters the 'soil_data' data correctly. All elements in soil data ('soil_data') must be characters defined in the soil keys ('soil_key'). Both soil_key and soil_data are lists. Consider an example: INPUT: soil_key = ['C', 'Clay', ' B', 'Bedrock', ' V', 'Void'] soil_data1 = [ ['V', 'C', 'V'], ['C', 'V', ' '], ['B', 'M', 'B'] ] soil_data2 = [ ['B', 'C', 'V'], ['C', 'V', ' B'], ['B', 'C', 'B'] ] OUTPUT: soil_data1: check data again. Parsing failed! soil_data2: Parsing successfully. Write a python function that checks if the soil data is being entered correctly. Return True and print 'Parsing successfully' for correct data. Otherwise, return False and tells the user 'check data again. Parsing…True or False If there is a past estimation error, there is a need to replace the property immediately.Bug sort out and fix all. )
- Is it true or false? For storing and processing lists of data, individual variables are ideal.How to decide if your variable should be declared as an enum type or any other data types? Support your answer with examples. plz avoid copied answers, my assignment will be submitted through turnitin and plagiarism will be detected.# Create Custom Transformer Create a custom transformer, just as we did in the lecture video entitled "Custom Transformers", that performs two computations: 1. Adds an attribute to the end of the numerical data (i.e. new last column) that is equal to $\frac{x_1^3}{x_5}$ for each observation. In other words, for each instance, you will cube the $x_1$ column and then divide by the $x_5$ column. 2. Drops the entire $x_4$ feature column if the passed function argument `drop_x4` is `True` and doesn't drop the column if `drop_x4` is `False`. (See further instructions below.) You must name your custom transformer class `Assignment4Transformer`. Your class should include an input parameter called `drop_x4` with a default value of `True` that deletes the $x_4$ feature column when its value is `True`, but preserves the $x_4$ feature column when you pass a value of `False`. This transformer will be used in a pipeline. In that pipeline, an imputer will be run *before* this transformer. Keep…