Questions tagged [logistic-regression]

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Architecture for Logistic Regression with Arbitrary Number of Options

Suppose I want to design a neural network to choose one of several mutually exclusive options. This may normally be done via logistic regression, where the input of the network would be a [batch x ...
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How do we interpret the images of weights in logistic regression

The following images are a) The weights of a logistic regression model trained on MNIST. b) The sign of the weights of a logistic regression How do these images represent the weights? Would be ...
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What is meant by “the number of examples is reduced”, and why is this the case?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3.2. Logistic Regression, the author says the following: 3.2. Logistic ...
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Does the image is logistic regression or SVM, and why? [closed]

Does the image is logistic regression or SVM, and why?
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How to frame this problem using RL?

How should this problem be framed in the domain of RL for preventing users from exceeding their bank account balance and being overdrawn? For example, a user has 1000 in an account, and proceeds to ...
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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: ...
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1answer
28 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 ...
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36 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 ...
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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 ...
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49 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 ...
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42 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 ...
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45 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 ...
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Is logistic regression used for unconstrained or constrained optimisation problems?

Is logistic regression used for unconstrained or constrained optimization problems, and why?
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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) ...
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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 ...
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58 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 ...
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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{...
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183 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 ...
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35 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 ...
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53 views

How many parameter would there be in a logistic regression model used to classify reviews into “good” or “bad”?

Suppose we want to classify a review as good ($1$) or bad ($0$). We have a training data set of $10,000$ reviews. Also, suppose we have a vocabulary of $100,000$ words $w_1, \dots, w_{100,000}$. So ...
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410 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, \...