###### Qib. Report the mean, median, mini mum, maximum, and standard deviation for each numeric variable in the data set, titanic_all.csv
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- Please provide steps to answer this question: Your task is simple: use machine learning to create a model that predicts which passengers survived the Titanic shipwreck. Implement and train a classification model for the Titanic dataset (the dataset can be found here: https://www.kaggle.com/c/titanic). Please ignore the test set (i.e., test.csv) and consider the given train set (i.e., train.csv) as the dataset. What you need to do: 1. Data cleansing 2. Split the dataset (i.e., train.csv) into a training set (80% samples) and a testing set (20% samples) 3. Train your model (see details below) 4. Report the overall classification accuracies on the training and testing sets 5. Report the precision, recall, and F-measure scores on the testing setThe file UniversalBank.csv contains data on 5000 customers of Universal Bank. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign. In this exercise, we focus on two predictors: Online (whether or not the customer is an active user of online banking services) and Credit Card (abbreviated CC below) (does the customer hold a credit card issued by the bank), and the outcome Personal Loan (abbreviated Loan below). Partition the data into training (60%) and validation (40%) sets. a. Create a pivot table for the training data with Online as a column variable, CC as a row variable, and Loan as a secondary row variable. The values inside the table should convey the count. In R, use…Use the dataset songdata.csv to answer the following questions: Which band/artist says love the most (per song)? The least? Who is the most negative band in the data set (in terms of sentiment)? Positive? Which band has the "best" vocabulary? First define what "best" means and then write tidytext code to determine the answer. Can you predict who a song is by? Take Katy Perry and Taylor Swift (or 2 other artists with at least 50 songs each) and come up with 5-10 features for each song. Split data into train and test and see how accurate a model can be (use glm or rf). Submit a single pdf or word report that includes a short paragraph summary of what you did and your answer to each question, any figures/plots/tables generated, and the R code used at the end of the document. Code needs to be in R Download songdata.csv from github using this link - https://github.com/ugis22/music_recommender/tree/master/content%20based%20recommedation%20system
- Use the dataset songdata.csv to answer the following questions: Which band/artist says love the most (per song)? The least? Who is the most negative band in the data set (in terms of sentiment)? Positive? Which band has the "best" vocabulary? First define what "best" means and then write tidytext code to determine the answer. Can you predict who a song is by? Take Katy Perry and Taylor Swift (or 2 other artists with at least 50 songs each) and come up with 5-10 features for each song. Split data into train and test and see how accurate a model can be (use glm or rf). must be written in R code to use with R studio.Go to UCI data repository (https://archive.ics.uci.edu/ml/datasets.php) and identify two data sets, one for estimation/regression and one for classification. Using Microsoft Excel or any other statistical software: a. Develop and interpret a linear regression model. b. Develop and interpret a logistic regression model. Note: Answers must be in your own words.30 B) (circle one in each bracket) In comparison to BubbleSort,SelectionSort tends to make:[more || fewer] comparisons[more || fewer] data movements
- 2. Activity Details: 1. Create randomdata for your plot can be created by setting seed-set.seed() function to 10, then using a uniform distribution using rnorm() for 1000 values for both x and y. Find any of the following data from open data sources found in the web a. Election Data b. Company Sales Data c. Covid 19 Data d. Population Data Create 2 separate plots, 1 for the randomized data, 1 for the data coming from open data sets. Remember to: a. Label the plotting area respective to the data b. Use a regression linepopulation_df = pd.read_csv('https://raw.githubusercontent.com/Explore-AI/Public-Data/master/AnalyseProject/world_population.csv', index_col='Country Code') Question 1: 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:- ?????ℎ_????=???????_????_??????????−????????_????_??????????????????_????_?????????? 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…This is a third time to uploading question every time expert giving wrong answer. R Code 1. Take the mtcars inbuilt dataset 2. split the dataset into 2 part train adn test with proper combination of size 3. Build a two different model of classification algorithm 4. plot the accuracy 5. plot the confusion matrix
- https://1drv.ms/x/s!Av-KKmo42J4EgXJFqbsHsb_jUdpA 1) The baseball worksheet contains US baseball player's team, position, and salary. Determine how many times the mode of baseball player’s salary is appeared in the data set? Group of answer choices 16 28 21 18 2) The baseball worksheet contains US baseball player’s team, position, and salary. Determine the shape of the distribution of baseball player’s salary and skewness value. Group of answer choices 1.84 and moderately skewed to left 1.84 and Highly skewed to right -1.84 and moderately skewed to right -1.84 and highly skewed to Left 3) The baseball worksheet contains US baseball player’s team, position, and salary. what is the second quartile of baseball player’s salary? Group of answer choices 4010021 4010054 1880000 1950347Please answer I'll Upvote you, Regarding the COVID Dataset ----------------------------- The dataset has been collected from the Directorate General of Health Services, Bangladesh. The dataset has 626 rows and 4 columns. The dataset contains the number of COVID tests performed, number of persons tested positive and number of death cases for each day. In the Regression model, you must implement the following algorithms.1. Linear Regression2. Polynomial Regression3. Lasso Regression4. Ridge Regression5. Elasticnet RegressionUsing R How would I create a plot for a specific day or range of days from an imported data set? Data Each row represents one day’s worth of covid numbers for a specific state where the columns represent: Date State Number of Cases Number of Deaths Exploratory Data Analysis For a single day (pick any day you want, BUT, be sure to specify which day you picked): Plot the number of cases and number of deaths for all states. (Choose any R plotting function you want.) Submit your R code. Now extend your analysis across 10 days. Create a single plot that visualizes the number of deaths per state across the 10 days, and a single plot that visualizes the number of cases across the 10 days. Submit your R code