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- Q3. The given coordinates are (0,0), (0,2),(2,0),(2,2) for representing a rectangle/square ,you are expected to find x-shearing where shearing parameter towards x-direction is 2 units. Also you are expected to find y-shearing if the shearing parameter towards y-direction is 3 units. Draw the objects before and after shearing. (Note: You are expected to use matrix representation in calculating the required values)Correct answer will be upvoted else Multiple Downvoted. Don't submit random answer. Computer science. You have n particular focuses (x1,y1),… ,(xn,yn) on the plane and a non-negative integer boundary k. Each point is a tiny steel ball and k is the draw in force of a ball when it's charged. The draw in power is something very similar for all balls. In one activity, you can choose a ball I to charge it. When charged, all balls with Manhattan distance all things considered k from ball I move to the situation of ball I. Many balls may have a similar facilitate after an activity. All the more officially, for all balls j with the end goal that |xi−xj|+|yi−yj|≤k, we dole out xj:=xi and yj:=yi. An illustration of an activity. Subsequent to charging the ball in the middle, two different balls move to its position. On the right side, the red dab in the middle is the normal situation of those balls. Your errand is to observe the base number of activities to move all balls to a similar…Correct answer will be upvoted else downvoted. Computer science. You and your companions live in n houses. Each house is situated on a 2D plane, in a point with integer organizes. There may be various houses situated in a similar point. The chairman of the city is requesting you for places for the structure from the Eastern show. You need to track down the number of spots (focuses with integer arranges), so the outline distance from every one of the houses to the show is insignificant. The display can be inherent a similar point as some house. The distance between two focuses (x1,y1) and (x2,y2) is |x1−x2|+|y1−y2|, where |x| is the outright worth of x. Input First line contains a solitary integer t (1≤t≤1000) — the number of experiments. The principal line of each experiment contains a solitary integer n (1≤n≤1000). Next n lines portray the places of the houses (xi,yi) (0≤xi,yi≤109). It's reliable that the amount of everything n doesn't surpass 1000. Output For…
- For the Linear Congruential method, assume the following parameters:Xo = 23,947, a = 2,902, c = 15,853 and M = 491.Feeling free to state any assumptions you deem necessary, define the first 10 random numbers.1. The impulse response of a causal system is: h(t) = A cos(wt) e¯¹/¹u(t) where u(t) is the Heaviside step function. The response is measured experimentally with a sampling interval of T. a. Write an expression for the sampled impulse response h[n]. b. Calculate the z transform of h[n] and write an expression for H[z]. Use the tables provided below as necessary. c. Does the system have an infinite impulse response (IIR) or finite impulse response (FIR)? Justify your answer. d. What is the DC gain of H[z]? e. Write a difference equation that describes the output y[n] in terms of input x[n].You build a model predicting blood pressure as a function of three variables: weight (numeric) age (numeric) income (categorical: low, medium, high) You first specify your model as: blood pressure ~ age * income + weight How many parameters (k) does your model have? (Remember, we do not count the grand mean in k) You change the above model specification to be: blood pressure ~ age * income + weight * income How many parameters does your model have now? You change your model to include the three-way interaction (which, remember, includes all two-way interactions and main effects, too!) Your model now looks like this: blood pressure ~ age * income * weight How many parameters does your model have now?
- Theoretical Overview Suppose we have a set of data consisting of ordered pairs and we suspect the x and y coordinates are related. It is natural to try to find the best line that fits the data points. If we can find this line, then we can use it to make all sorts of other predictions. In this project, we're going to use several functions to find this line using a technique called least squares regression. The result will be what we call the least squares regression line (or LSRL for short). In order to do this, you'll need to program a statistical computation called the correlation coefficient, denoted by r in statistical symbols: NOTE: Equation is written assuming you start at the value 1. Lists start at index 0. Once you have the correlation coefficient, you use it along with the sample means and sample standard deviations of the x and y-coordinates to compute the slope and y-intercept of your regression line via these formulas: Tasks: In this project, you must read…Which qualities are preferred for an estimator? (Select all that apply.) Not centered around the unknown parameter Variability is small Centered around the unknown parameter Variability is largeThe following table contains output from a lasso fit to a linear model with d= 5 variables and n = 65 observations. Starting from the left, the columns are X, and B₁, ..., B5, i.e. each row has X and the transposed column vector B¹(X). 0.00000 0.00000 -0.04596 0.08497 0.04129 -0.08195 -0.00764 0.22778 -0.04274 0.07868 0.03430 -0.07599 0.00000 1.96117 -0.02092 0.04606 0.00000 -0.04090 3.28220 0.00000 0.02263 0.00000 -0.02105 4.49485 0.00000 0.00375 0.00000 0.00000 4.73846 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 You will perform computations using this table and report your results. A) Compute the maximum value of the L₁ norm for vectors of coefficients attained in this table, that is compute maxx ||3¹(A)||₁ B) Consider the 2nd breakpoint from the top of the table, namely the breakpoint corresponding to A-0.22778. Compute the L₁ norm for the vector of coefficients at this point in the path, i.e. compute || (0.22778)||1 C) For the same 2nd breakpoint in the table, compute…
- Suppose X|Y=1 is a Uniform(0,4) density, X|Y=0 is a Uniform(2,6) density, and P(Y=1) = 2/3. Calculate the Bayes error, i.e., the error rate of the Bayes classifier (you may leave your answer as a fraction).True or false: In RapidMiner, the label (dependent variable) can be coded either alphabetically (e.g., true/false) or numerically (e.g., 0/1). True or false: The Logistic Regression operator in RapidMiner offers only one algorithm for model creation.In a rehabilitation study, a joystick is used to measure applied wrist force during a target tracking exercise. What random variable would best describe the difference between the true force and the measured force? Write MATLAB code for a likelihood function for the measured force given the true force.