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Using pytorch, a user implemented linear regression and received the following error

import torch from torch.autograd import Variable import torch.nn as nn import torch.nn.functional as F x_data=Variable(torch.Tensor([[10.0],[9.0],[3.0],[2.0]])) y_data=Variable(torch.Tensor([[90.0],[80.0],[50.0],[30.0]])) class LinearRegression(torch.nn.Module): def __init__(self): super(LinearRegression,self).…

Data Science

Answered Jan 15, 2020 · 838 Views Read answer →

A user is trying to run a linear regression for 2 columns of data (IMF_VALUES, BBG_FV)and got the following error

TypeError Traceback (most recent call last) in () 1 regression = linear_model.LinearRegression ----> 2 regression.fit(IMF_VALUE, BBG_FV) TypeError: fit() missing 1 required positional argument: 'y' The following code is given below import numpy as np from sklearn import linear_model import matplotlib.pyplot as plt…

Data Science

Answered Jan 15, 2020 · 824 Views Read answer →

A user implemented linear regression using Numpy and linear algebra and received an error.

def linear_function(w , x , b): return np.dot(w , x) + b x = np.array([[1, 1,1],[0, 0,0]]) y = np.array([0,1]) w = np.random.uniform(-1,1,(1 , 3)) print(w) learning_rate = .0001 xT = x.T yT = y.T for i in range(30000)

Data Science

Answered Jan 15, 2020 · 864 Views Read answer →

A user is using linear regression with the below code and got the following error

from math import * f=open("data_setshort.csv", "r") data = f.readlines() f.close() xvalues=[]; yvalues=[] for line in data: x,y=line.strip().split(",") x=float(x.strip()) &

Data Science

Answered Jan 15, 2020 · 941 Views Read answer →

Differentiate linear regression from logistic regression

The differences between linear and logistic regression are Linear regression is used when the dependent variable is continuous and logistic regression is used when the dependent variables are categorical in nature. Linear regression uses straight line equation y=mx+c but logistic regression uses the equation y=ex+e-x…

Data Science

Answered Jan 15, 2020 · 1.0K Views Read answer →

A user is implementing a univariate linear regression on python but the code output NaN for theta after going to infinity. How to fix that?

# implementation of univariate linear regression import numpy as np def cost_function(hypothesis, y, m): return (1 / (2 * m)) * ((hypothesis - y) ** 2).sum() def hypothesis(X, theta): return X.dot(theta) def gradient_descent(X, y, theta, m, alpha): for i in range(1500):

Data Science

Answered Jan 15, 2020 · 954 Views Read answer →

A user tried to implement linear regression using matplotlib but gives a value error. How to fix that?

Data Science,matplotlib,Machine Learning

Data Science

Answered Jan 15, 2020 · 838 Views Read answer →

How can VIF avoid multicollinearity issues in a linear regression model?

Word2Vec uses a neural network to represent words whose hidden network encodes the representation into vectors. On the other hand, FastText breaks words into several n-grams and train on the data. For instance, the tri-grams for the word apple is app, ppl, and ple (ignoring the starting and ending of boundaries of…

Data Science

Answered Jan 15, 2020 · 928 Views Read answer →

How to visualize a linear regression model in R?

# Simple Linear Regression # Importing the dataset dataset = read.csv('Salary_Data.csv') # Splitting the dataset into the Training set and Test set # install.packages('caTools') library(caTools) set.seed(123) split = sample.split(dataset$Salary, SplitRatio = 2/3) training_set = subset(dataset, split == TRUE) test_set…

Data Science

Answered Jan 15, 2020 · 926 Views Read answer →

Explain a simple linear regression in R

# Simple Linear Regression # Importing the dataset dataset = read.csv('Salary_Data.csv') # Splitting the dataset into the Training set and Test set # install.packages('caTools') library(caTools) set.seed(123) split = sample.split(dataset$Salary, SplitRatio = 2/3) training_set = subset(dataset, split == TRUE) test_set…

Data Science

Answered Jan 15, 2020 · 838 Views Read answer →

Explain a simple linear regression in Python

# Simple Linear Regression # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('Salary_Data.csv') X = dataset.iloc[:, :-1].values y = dataset.iloc[:, 1].values # Splitting the dataset into the Training set and Test set from…

Data Science

Answered Jan 15, 2020 · 912 Views Read answer →

How to remove columns showing multicollinearity in a regression model?

# Multilinear Regression import pandas as pd import numpy as np import matplotlib.pyplot as plt # loading the data cars = pd.read_csv("E:\Bokey\Excelr Data\Python Codes\all_py\Multilinear Regression\cars.csv") # to get top 6 rows cars.head(40) # to get top n rows use cars.head(10)

Data Science

Answered Jan 15, 2020 · 1.2K Views Read answer →