Business analytics. R programming 1. Import HouseData.csv with stringsAsFactors = FALSE to a home data frame. Factor() Parking and City_Category vectors.
Q: Write a program in MATLAB that will return the corner elements of a 10-by-10 matrix? Please show…
A: The corner elements of a 10-by-10 matrix can be retrieved as follows: Upper left corner has the…
Q: Show how you can use the visual model to subtract (3)/(1)
A: To subtract (3)/(1), we can use a visual pattern called fraction bars or fraction bars. We can do…
Q: Use scipy.stats and matplotlib.pyplot from Python to plot the cdfs of the Gamma(1, 1) and Gamma(2,…
A: Here we can write the python code for this given problem and attach the output for this , so the…
Q: Business analytics programming. R programming Import HouseData.csv with stringsAsFactors = FALSE…
A: In this question we have to write a R program where we need to Import HouseData.csv with…
Q: Data Exploration: The Iris dataset is used for data exploration, using Python. Understand your…
A: Input : Load the Iris dataset using library functions Output : Create box plots. Identify…
Q: Different approaches to express patterns exist. Please discuss and explain each of the following…
A: Given: To discuss pattern representation. The digital world is all about pattern. A pattern might be…
Q: web design Construct a Movie class in Model architecture. Subsequently, write a method called…
A: we create a small class diagram of movie:in which: 1.we create a movie attribute and a category…
Q: Calculate RMSE on the validation set. What is it equal to? Provide the answer, rounded to the…
A: 7.Answer: I have written code in python
Q: Step 1. Intersection over Union def intersection_over_union(dt_bbox, gt_bbox): ---> return iou Step…
A: Coded using Python 3.
Q: TODO 7 To start off, we can plot each feature against every other feature just to see if there…
A: In this task, the goal is to plot a scatter matrix of the features in the forestfire_df DataFrame.…
Q: We created a model (Im) using LinearRegression from sklearn library. We got the data from the cars…
A: Given that, The name of the model created using Linear Regression from sklearn library is lm. From…
Q: Give an example of an inrrelevent feature for the task of predicting emlpoyee salary.
A: The problem is based on the basics of feature selection in data science and machine learning.
Q: Can we combine data with maps? Explain why this is or is not useful.
A: Here is the explanation regarding adding the data to the maps.
Q: For each n-element array an, the first element is always what is returned by a[1]. What is true, and…
A: An array is a collection of items of the same data type stored at contiguous memory locations. We…
Q: rs(iris[,1:4], main = ‘‘Iris Data’’, pch = 20, col = unclass(iris$Species) + 2). Use R to create a…
A: Given :- pairs(iris[,1:4], main = ‘‘Iris Data’’, pch = 20,col = unclass(iris$Species) + 2).…
Q: create a matrix that has multiple rows, separate the rows with semicolons.
A: We can create an 3x3 matrix having multiple rows, the rows are separated by the spaces. The snippet…
Q: Describe the split that exists between descriptive and inferential statistics.
A: Descriptive and Inferential statistics: In a word, descriptive statistics are concerned with…
Q: create multiple graphs with single_call to plot, these statements plot three related functions of x:…
A: The objective is to create multiply graphs with single_call to plot. These statements plot three…
Q: Explore the relationship between data binding and the Observer pattern.
A: In software development, especially when it comes to creating user interfaces (UI) two important…
Q: Frames are a type of data structure used in artificial intelligence for representing stereotypical…
A: The objective of the question is to identify the possible properties or attributes that a frame…
Q: 1. What further questions would you ask on the evaluation? Think of test data, metrics, and…
A: You're the ChiefData Science Officer at a large bank. You've instructed your team to experiment with…
Q: Step 3. Evaluate Model To assess the quality of the model, we will use the mAP metric defined as AP…
A: Coded using Python 3.
Q: Different approaches to express patterns exist. Please discuss and explain each of the following…
A: Introduction: To discuss pattern representation. The digital world is all about pattern. A pattern…
Q: Multidimensional scaling can work as long as we have the pairwise distances between objects. We do…
A: let’s say you had a set of cities in Florida and their distances:
Q: R studio You need to generate 300 random integer values with normal distribution (mean = 0 and…
A: We need to generate the 300 random variable. The rnorm function is used to generate integer values…
Q: TODO: Lienar Regression with least Mean Squares (LMS) Optimize the model through gradient descent.…
A: To complete the TODOs for the LeastMeanSquares class, you need to implement the fit and predict…
Q: Please provide the code and explanation for the following in R for One Way ANOVA with the penguins…
A: Load the penguins dataset from the palmerpenguins library. Create a new dataframe containing only…
Q: from sklearn.linear_model import LogisticRegression From this library give me example code…
A: from sklearn.linear_model import LogisticRegression From this library give me example code for…
Q: Fill the blank : 1- From the output given below identify...................for Business Department…
A: here have to determine correct option for given html problem.
Q: question 2) what is the difference between correlation and convolution filtering methods? Briefly…
A: Dear Student, The only difference between Correlation And Convolution matrix is that in Correlation…
Q: Using the beans dataset, Build a CNN network to perform image classification using TensorFlow. Does…
A: By using the following step you can build a CNN network for image classification using the Beans…
Q: The length of vectors in Word2Vec model is 2|V], where |V| represents the length of unique…
A: The answer is given below.
Q: Use elements of {0,0,0,0,0,1,1,0,2} and write a SciPy program for CSR Matrix.
A: The Answer is
Q: Software for business analytics. Coding in R Create a data frame called house and load HouseData.csv…
A: In today's business world, companies are generating massive amounts of data from various sources.…
Q: Write the related code using the look-at function to setup the model-view matrix.
A: Model view matrix 4×4 matrix encodes the 3-axis of a Cartesian coordinate system. For matrices you…
Business analytics. R
![](/static/compass_v2/shared-icons/check-mark.png)
Step by step
Solved in 3 steps
![Blurred answer](/static/compass_v2/solution-images/blurred-answer.jpg)
- Subject is actually Programming in Business Analytics. Programming in R 1. Import the data file HouseData.csv with an option stringsAsFactors = FALSEto a data frame and name it house. And then, use factor() to encodeParking and City_Category vectors as a factor#Code fits a regression 'ginven ~ ggdp+ci3+cinf'import wooldridge as wooimport numpy as npimport pandas as pdimport statsmodels.api as smimport statsmodels.formula.api as smfimport matplotlib.pyplot as pltIn a 384-well plate luciferase assay, we drugged 4 receptors (A, B, C, D) with their endogenous agonists at a range of doses. Below is a subset of the resulting data frame (please use the full data frame attached to the original email as a CSV file). Each row of this data frame corresponds to a single well of the 384 well plate. The columns are as follows: receptor: the receptor tested in the well agonist: the endogenous agonist used for a receptor agonist_nM: the dose of the endogenous compound (in nanomolar) ● RLU: raw luminescence of the well (our measure of receptor activity) To answer this 3 part question, we’ll ask you to submit a PDF file containing all of your source code, plots, and written interpretation. (Using something like a Jupyter Notebook with Python or Rmarkdown is recommended, but not required.) You should provide brief explanations of your thought process at each step. Part A: Different receptors have different basal rates of activity. To better facilitate…
- 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 AlignmentHorizontal 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 AlignmentTODO: Lienar Regression with least Mean Squares (LMS) Optimize the model through gradient descent. *Please complete the TODOs. * !pip install wget import osimport randomimport tracebackfrom pdb import set_traceimport sysimport numpy as npfrom abc import ABC, abstractmethodimport traceback from util.timer import Timerfrom util.data import split_data, feature_label_split, Standardizationfrom util.metrics import msefrom datasets.HousingDataset import HousingDataset class BaseModel(ABC): """ Super class for ITCS Machine Learning Class""" @abstractmethod def fit(self, X, y): pass @abstractmethod def predict(self, X): pass class LinearModel(BaseModel): """ Abstract class for a linear model Attributes ========== w ndarray weight vector/matrix """ def __init__(self): """ weight vector w is initialized as None """ self.w = None # check if the matrix is 2-dimensional. if…
- Examine the R expressionpairs(iris[,1:4], main = ‘‘Iris Data’’, pch = 20,col = unclass(iris$Species) + 2).Use R to create a similar expression to produce a scatter plot matrix of the variables mpg, disp, hp, drat,and qsec in the data frame mtcars. Use different colors to identify cars belonging to each of thecategories defined by the carsize variable.Horizontal sequence :VIRL Vertical sequence:MKF 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: V I R L M K F 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). V I R L M K F Align and score all optimal alignments here.Remove first and last element from likedlist JAVA
- What is meant by K-Map? What are its limitations, advantages and disadvantages?import numpy as np import pandas as pd from catboost import CatBoostRegressor from lightgbm import LGBMRegressor from sklearn.linear_model import Lasso from sklearn.metrics import mean_squared_error from sklearn.model_selection import train_test_split from xgboost import XGBRegressor df=pd.read_csv('data.csv') X = df.drop('shares', axis=1) y = df['shares'] from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.40, random_state=13) from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.25, random_state=13) Ans:- # code here Q- Now let's train our first model - XGBoost. A link to the documentation: https://xgboost.readthedocs.io/en/latest/ We will use Scikit-Learn Wrapper interface for XGBoost (and the same logic applies to the following LightGBM and CatBoost models). Here, we work on the regression task - hence we will use XGBRegressor. Read…Use elements of (0,0,0,0,0,1,1,0,2} and write a SciPy program for CSR Matrix.
![Principles of Information Systems (MindTap Course…](https://www.bartleby.com/isbn_cover_images/9781285867168/9781285867168_smallCoverImage.gif)
![Fundamentals of Information Systems](https://www.bartleby.com/isbn_cover_images/9781305082168/9781305082168_smallCoverImage.gif)
![Principles of Information Systems (MindTap Course…](https://www.bartleby.com/isbn_cover_images/9781285867168/9781285867168_smallCoverImage.gif)
![Fundamentals of Information Systems](https://www.bartleby.com/isbn_cover_images/9781305082168/9781305082168_smallCoverImage.gif)