Questions tagged [logistic-regression]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
1
vote
0answers
17 views

Neural network algorithm implementation for Iris dataset

I want to use Neural network algorithm over famous Iris dataset. Iris dataset attributes names sepal length in cm sepal width in cm petal length in cm petal width in cm Sample dataset: ...
1
vote
1answer
23 views

Back propagation approach to logistic regression: why is cost diverging but accuracy increasing?

Background I have tried to fit a logistic regression model - written using a forward / back propagation approach (as part of Andrew Ng's deep learning course) - to a very non-linear data set (see ...
0
votes
1answer
32 views

Hyper-plane in logistic regression vs linear regression for same number of features

Geometric interpretation of Logistic Regression and Linear regression is considered here. I was going through Logistic regression and Linear regression. In the optimization equation of both following ...
0
votes
0answers
32 views

Given the same features, do logistic regression and neural networks produce the same output?

I have a binary classification problem. I have variables (features) var1, var2, var3, ..., var14. Using these variables (aka features) in a logistic regression, I get their weights. If I use the same ...
1
vote
1answer
45 views

How could logistic loss be used as loss function for an ANN?

Normally, in practice, people use those loss functions with minima, e.g. $L_1$ mean absolute loss, $L_2$ mean squared error, etc. All those come with a minimum to optimize to. However, there's ...
1
vote
1answer
37 views

Why is the hypothesis function $h_{\theta}(x)$ equivalent to $E[y | x; \theta]$ in generalised linear models?

Reading through the CS229 lecture notes on generalised linear models, I came across the idea that a linear regression problem can be modelled as a Gaussian distribution, which is a form of the ...
2
votes
1answer
42 views

How does the weight update formula for logistic regression work?

I am trying to use Logistic Regression to make a spam filter, but I am having trouble understanding the weight update part. I have processed my email dataset, and I have an attribute vector of the top ...
2
votes
0answers
33 views

Is logistic regression used for unconstrained or constrained optimisation problems?

Is logistic regression used for unconstrained or constrained optimization problems, and why?
2
votes
1answer
44 views

Is it compulsary to normalize the dataset if doing so can negatively impact a Binary Logistic regression performance?

I am using raw data set with 4 feature variables (Total Cholesterol, Systolic Blood Pressure, Diastolic Blood Pressure, and Cigraeette count) to do a Binominal Classification (find stroke likelihood) ...
3
votes
2answers
922 views

Why not use the MSE instead of the current logistic regression?

When watching the machine learning course on Coursera by Andrew Ng, in the logistic regression week, the cost function was a bit more complex than the one for linear regression, but definitely not ...
1
vote
1answer
57 views

Checking Whether Given Logistic Regression Classifier classifies data

A bank wants to decide whether a customer can be given a loan, based on two features related to (i) the monthly salary of the customer, and (ii) his/her account balance. For simplicity, we model ...
2
votes
0answers
61 views

How to define cost function for custom nonlinear functions?

For logistic regression, the Cost function is defined as: \begin{equation} Cost(h_{\theta}(x)-y) = -ylog(h_{\theta}(x))-(1-y)log(1-h_{\theta}(x)) \end{equation} I now have a nonlinear function \begin{...
2
votes
0answers
121 views

What is the right formula for weight update rule in Logistic Regression using stochastic gradient descent

Apologies for the lengthy title. My question is about the weight update rule for logistic regression using stochastic gradient descent. I have just started experimenting on Logistic Regression. I ...
0
votes
0answers
34 views

How can the bias and the coefficient be calculated in logistic regression?

How can the bias, $b_0$, and the coefficient for the single input value, $b_1$, be calculated in logistic regression? I am trying to calculate these coefficients with pure Python. Can anybody ...
4
votes
1answer
371 views

Is logistic regression more free from the conditional independence assumption than naive Bayes?

To my understanding, logistic regression is an extension of naive Bayes. Suppose $X = \{x_1, x_2, \dots, x_N \}$ and $Y = \{0, 1\}$, each $x_i$ is i.i.d and $P(x_i \mid Y=y_k) \sim \mathcal{N}(\mu, \...