Write code of doing logistic regression on numerical data.
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Write code of doing logistic regression on numerical data.
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- Implement a logistic regression model from scratch using Python. Assume you have a dataset containing features and binary labels (0 or 1). Your task is to write a Python class that trains a logistic regression model using gradient descent optimization.Write short notes on: Lasso RegressionTheoretical 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…
- Write python code to do the followings 1. Read the attached file "Breast_cancer_dataset.co and store all its columns (except classification) inta a variable (X), and read column "classilication" into a variable (V). Note that if Classification-1 means patient is Healthy, and Classification=2 means patient has Breast cancer 2. Use the package below to train a logistic regression model to learn to predict whether a patient has breast cancer or not using the variables X and Y. from sklearn.linear model iaport Logistietegression 3 Predict the class of a patient. Choose any patient from the input file "Breast cancer_dataset.cs, 4. Compute error in whichever way you prefer. S. Use your model to show the feature/attribute that has the highest impact on Breast cancer. Print the name of the attribute. Explain your findings in one line. The assignment is out of 5 marks. Each one of the above points weighs one grade. Any unnecessary (or extra) lines of code will deduct grades.Computer Science we have a data set , how to split the sample into a training set and a test set. Training set is all firms with names starting with “A-G”, and test set is all firms with names starting with “H-L” in Python?Write an order to generate binomial data with the number of observations (n) being 50, the number of trials (size) being 5 and the probability of success being 0.5, then storing the results in the binomial data matrix, with the number of columns being 5.
- KNN is a technique used to estimate new values based on the similarity of known ones. In this assignment, your company wants you to estimate the selling price of a customer's building The price you calculate will be given to the customer as the company selling price recommendation. You decide to use Data Science techniques such as the K-Nearest Neighbor.(KNN) You will need to: Import the necessary libraries from your program. (You can use the model class sklearn.neighbors.KNeighborsClassifier, part of the package sci-kit-learn 1.1.1 (Links to an external site) or any other. Train/test the model with the data included in the module (cal_housing.tgz). The house you need to estimate the value for has the following properties: longitude: 120.75latitude: 39.34housingMedianAge: 35.5total rooms: 260totalBedrooms:120 population:540households: 12medianIncome:1.8 K BuildingValue: ? What is the recommended price? You need to provide the code, properly commented. You could use…ASSIGNMENT The Injury Severity Score (ISS) is a medical score to assess trauma severity. Data on ISS and hospital stay (in days) have been collected from a number of patients who were admitted to hospital after accidents. The ISS data are [64 35 50 46 59 41 27 39 66], and the length of stay data are [8 2 55 4 3 1 4 6]. Use MATLAB to plot the relationship between ISS and hospital stay.ACan you describe the difference between descriptive and inferential statistics?
- Write a computer code to do linear regression analysis of a given dataset to find the relation between two variables which gives the least sum of squares error. Using Excel or Matlab. Include a copy of the script, a sample input, and a sample output from your codes. Sample output must include modelfit parameters and the sum of the squared errors for the fit. Please also run the code for thefollowing data set to find and report the relation between y and x:x y25 3040 80120 15075 80150 200300 350270 240400 320450 470575 583let's fill in the blanks• Give your own example of a type 1 and type 2 error Why do we use train.test,split() function from Python when analyzing data? What is the point of splitting data? • What is the bias vs. variance tradeoff?