Kadd_to Logisticregressiondef fit(self, x, Y, epochs-100e, print_loss=True):This function implements the Gradient Descent AlgorithmArguments:x -- training data matrix: each column is a training example.The number of columns is equal to the number of training examplesY -- true "label" vector: shape (1, m)epochs --Return:params --dictionary containing weightslossesloss values of every 100 epochs--grads --dictionary containing dw and dw_elosses = []for i in range(epochs):# Get the number of training examplesm = x. shape[1]### START YOUR CODE HERE #### Calculate the hypothesis outputs A (* 2 lines of code)Z =A =# Calculate loss (* 1 line of code)loss =# calculate the gredients for w and w_edw =dw_e =# weight updatesself.W =self.w_e =### YOUR CODE ENDS ###

Answer: We have complete the function. also attached the code in next page.

Answered: Xadd_to LogisticRegression def…

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Cs10-8L_B21_3Q2122 ASSESSMENTS Matlab Activity 2-1 My Solutions > Factoring Create a simple MATLAB CODE that will factor out the following expressions and save it on the specified variable: factor Prime factors. factor(N) returns a vector containing the prime factors of N. This function uses the simple sieve approach. It may require large memory allocation if the number given is too big. Technically it is possible to improve this algorithm, allocating less memory for most cases and resulting in a faster execution time. However, it will still have problems in the worst case. Factor the following expressions and place your answer on the indicated variable. 1. Expressionl =- 25, save your answer to Factorl 2. Expression2 =+x-4x + 2x - 12, save your answer to Factor2 3. Expression3 =- 10x + 25, save your answer to Factor3 4. Expression4 = 12x- 12xy + 3xy - 3x, save your answer to Factor4 5. Expressions = rz-3- 2xyz + 6xy + x2 - 3xz + y'z- 3y - yz + 3yz, save your answer to Factor5 Script e…
Sort function false true is used in MATLAB to arrange elements from larger to smaller While loop function is used in case of no number of repetitions is defined To delete data in workspace, we can use clc command Length function is used to know the size of matrix in MATLAB
link to MINST code: https://www.dropbox.com/s/i21pedejv0sknnq/MINST.pdf?dl=0 1) Add a confusion matrix to the MNIST code example from the link provided. Set the epochs parameter to 5. Explain which entry of the matrix yields the number of ones (the number 1) that are falsely recognized as eights (the number 8). (If you use indices in your explanation, use the Python index notation, i.e., start at zero.) Run your code a few times. Is the confusion matrix always the same? Briefly explain.
False True There are three types of vectors in MATLAB Sort function is used in MATLAB to arrange elements from larger to smaller While loop function is used in case of no number of repetitions is defined To delete data in workspace, we can use clc command Length function is used to know the size of matrix in MATLAB
%Encode A1, b1 and x1 as the vector of unknowns. A1 = b1 = syms xv1 = %Check the size of A, set it as m1 and n1 [m1,n1] = %Augment A and b to form AM1 AM1 = %Solve the Reduced Rwo Echelon of AM1. RREFA1 = %Collect the last column and set as bnew1, set the remaining elements as Anew1 bnew1= Anew1 = %Check if Anew is an identity matrix, if it is, bnew is the solution if Anew1 =eye(m1,n1) Root1 = bnew1 else display("No Solution") end %Augment the matrix A1 with the identity Matrix of the same size, set the result as AMI1 AMI1 = %Find the reduced row echelon form of AMI1, set the result as RREFAI1 RREFAI1= %Collect the second half of the matrix as AInew1, set the remaining elements as AIold1 AInew1= AIold1 = %Check if AIold1 is an identity matrix, if it is, AInew1 is the inverse %Encode A2, b2 and xv2 as the vector of unknowns. A2 = b2 = syms xv2 = %Check the size of A2, set it as m2 and n2 [m2,n2] = %Augment A2 and b2 to form AM2 AM2 = %Solve the…
def weighted_mse_grad(w, X, y, V):"""Calculate gradient of the weight MSE loss in the given point w Parameters----------w: array_likeCurrent point, in which we want to evaluate gradient (vector with k+1 elements)X: array_likeDesign matrix with N rows and k+1 columnsy: array_likeVector with N observations of the target variableV: array_likeDiagonal matrix N x N, with the weightsReturns----------out: ndarrayvector of gradient, k+1"""# your code here # TEST weighted_mse_grad()w = np.zeros(5)X = np.random.randn(10, 5)y = np.ones(10)V = np.diag(np.ones(10)) L_grad = weighted_mse_grad(w, X, y, V)assert(L_grad.shape == (5,)) w = np.zeros(5)X = np.eye(5)y = np.ones(5)V = np.diag(np.ones(5))L_grad = weighted_mse_grad(w, X, y, V)assert(L_grad.shape == (5,)), 'The shape of the output on the test case is wrong'assert(np.allclose(5 * L_grad,- y * 2)), 'The values of the output on the test case is wrong'
In a CS department top 3 students' marks are compared to develop the similarity graph. Students name are Alia, Kareem and Fiza. Each student is enrolled in 5 subjects (Data Structures, Discrete math, calculus, Operating system and Database management systems). Your task is to fill the arrays with user input and the values should be between 80 and 100 (80 and 100 are inclusive) for each subject. Now compare these three arrays and find the common numbers between them and put them in a separate array. Write in C++.
The formula C=numpy.add(A, B) adds the two matrices A and B and stores the result in C.• To subtract matrix B from matrix A, enter C=numpy.subtract(A, B). The result is stored in C.• C=numpy.divide(A, B): Split matrix A into two equal parts and store the result in C.• C stands for numpy.multiply(A, B): Multiply matrices A and B, then store the result in matrices C.• C=numpy.sum(A): Calculate the sum of each element in the matrix A, then store the result in c R.• C=numpy.sum(A, axis = 0): Create a vector C by adding the columns of the matrix A.• C=numpy.sum(A, axis = 1): Summarize matrix A row-by-row and store the result in the vector C. Create Python code that demonstrates the use of these techniques in a sample matrix.
Horizontal sequence :RIVL Vertical sequence:FMK Scoring rules: g/o = -3, g/e = -1, match or mismatch - from PAM250 substitution matrix below. SW algorithm. 1. Complete the scoring matrix. Scoring matrix with PAM250 scores: R I V L F M K 2. Set up, initialize and complete the SW matrix. 3. Retrace, align and score alignment(s). Use the arrows and circles for the matrix and path(s). R I V L F M K Align and score all optimal alignments here. PLZ the arrows and circles for the matrix and path(s) AND SHOW ALL possible Alignment
Horizontal sequence :RIVL Vertical sequence:FMK Scoring rules: g/o = -3, g/e = -1, match or mismatch - from PAM250 substitution matrix below. NW algorithm. 1. Complete the scoring matrix. Scoring matrix with PAM250 scores: R I V L F M K 2. Set up, initialize and complete the NW matrix. 3. Retrace, align and score alignment(s). Use the arrows and circles for the matrix and path(s). R I V L F M K Align and score all optimal alignments here. PLZ the arrows and circles for the matrix and path(s) AND SHOW ALL possible Alignment
Linear Equation SystemLU Decomposition Method AlgorithmDecomposition phase The LU Decomposition (Doolittle) method has the following properties: The U matrix is identical to the upper triangular matrix resulting from the Gaussian Elimination;The elements at the bottom below the main diagonal of the matrix L are the multipliers used during the Gaussian Elimination, that is, Li*j is the multiplier that eliminated Ai*j.It is common practice to store the multipliers at the bottom of the coefficient matrix, replacing the coefficients as they are eliminated (Li*j replacing Ai*j) The diagonal elements of L do not need to be stored, as their values are understood to be unitary. The final form of the coefficient matrix would be the mixture of L and U: The initial part of the LU Decomposition Method algorithm is identified with Gaussian Elimination, except that each λ multiplier is now stored in the lower triangular portion of matrix A: solve the system of linear equations followed by the…
The command (find) is -:used to O O find the maximum number within a matrix find the minimum number within a matrix extract the numbers satisfying a condition evaluate the average of a group of numbers determine the locations of numbers satisfying a condition O O

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