# Questions tagged [linear-regression]

For questions related to the theory or application of linear regression.

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### Is there a connection between the bias term in a linear regression model and the bias that can lead to under-fitting?

Here is a linear regression model $$y = mx + b,$$ where $b$ is known as $y$-intercept, but also known as the bias , $m$ is the slope, and $x$ is the feature vector. As I understood, in machine ...
65 views

### Which of the following two implementations of a Least Squares classifier in Python is correct?

I am trying to solve a classification problem by implementing the Least Squares algorithm in Python. To solve this problem, I am implementing the linear algebra formula to train the classifier, which ...
98 views

### Is there any domain in machine learning that solves a problem by using only analytical algorithms?

Most of the algorithms in machine learning I am aware of use datasets and learning happens in an iterative manner given some examples. The examples can also be understood as experience in the case of ...
46 views

### Difficult to build learning curve for a simple linear regression

In some part of my online ML course, I should build a code for plotting a learning curve, to be more specific, it's just a linear regression implementation. So the first thing to consider is the ...
26 views

### Fine tuning a BERT model for text classification

An article written by Jay Alammar (http://jalammar.github.io/a-visual-guide-to-using-bert-for-the-first-time/) on using a BERT transformer for text classification. The article mentions the following ...
83 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 ...
74 views

### What ML algorithm should I use that suits this data?

What if I have some data, let's say I'm trying to answer if education level and IQ affect earnings, and I want to analyze this data and put in a regression model to predict earnings based on the IQ ...
99 views

### multi vs one prediction using Regression

I was trying to build a prediction system where I have the input data arranged in multiple columns. The input data would be of the type where I have weather, service type (bronze, silver, gold), size ...
54 views

### Assumptions of a Linear Regression [closed]

I was going through the concept of Linear Regression and ran into the concept of deciding whether a Linear Regression Model is the best fit for your data by 5 assumptions: Linearity Homoscedasticity ...
29 views

### Which machine learning technique can I use to match one set of data points to another?

I have two measuring devices. Both measure the same thing. One is accurate, the other is not, but does correlate with a non-fixed offset, some outliers, and some noise. I won't always be using the ...
7 views

### Hand-crafted regression overshoots despite learning rate provided from hessian of the loss

I tried to do my own linear regression but I have seen that there are differences with LinearRegression from sklearn. Indeed, ...
53 views

### How can you grade an input?

I'm wondering how one can apply linear regression or some other method to calculate a grade/score for an input. More specifically, I'm having multiple objects in 2D-space, with some (but not all) of ...
1k views

### What to do if CNN cannot overfit a training set on adding dropout?

I have been trying to use CNN for a regression problem. I followed the standard recommendation of disabling dropout and overfitting a small training set prior to trying for generalization. With a 10 ...
57 views

### Would either $L_1$ or $L_2$ regularisation lower the MSE on the training and test data?

Consider linear regression. The mean squared error (MSE) is 120.5 for the training dataset. We've reached the minimum for the training data. Is it possible that by applying Lasso (L1 regularization) ...
232 views

### Is Deep Learning the repeated application of Linear Regression?

Is Deep Learning the repeated application of Linear Regression?
412 views

### Can we use the recursive least squares as a learning algorithm to an ADALINE?

I'm new to neural network, I study electrical engineering, and I just started working with ADALINEs. I use Matlab, and in their Documentation they cite : However, here the LMS (least mean squares) ...
31 views

### Linear output layer back propagation

So I'm stack to something that it's probably very easy but I can't get my head around it. I'm building a Neural Network that will consist of many layers with non-linear activation functions (probably ...
57 views

I am trying to comprehend how the Gradient Descent works. I understand we have a cost function which is defined in terms of the following parameters, $J(𝑤_{1},𝑤_{2},.... , w_{n}, b)$ the derivative ...
26 views

### Is there a UCB type algorithm for linear stochastic bandit with lasso regression?

Why is there no upper confidence bound algorithm for linear stochastic bandits that uses lasso regression in the case that the regression parameters are sparse in the features? In particular, I don't ...
63 views

### Is there any way to apply linear transformations on a vector other than matrix multiplication?

I am trying to optimize the cost function calculation in regression analysis using a non-matrix multiplication based approach. More specifically, I have a point $x = (1, 1, 2, 3)$, to which I want to ...
26 views

### Effect of adding an Independent Variable in Multiple Linear Regression

I am new in machine learning and learning linear regression concept. Please help with answers to below queries. I want to understand effect on existing independent variable(X1) if I add a new ...
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### How do we choose the activation function for each hidden node? [duplicate]

I am new to neural networks. I would like to use them as a fitting or forecasting method. A simple NN model that does not contain hidden layers, that is, the input nodes are directly connected to the ...
642 views

### Is there a machine learning algorithm to find similar sales patterns?

I have a dataset as follows (and the table extends to include an extra 146 columns for companies 4-149) Is there an algorithm I could use effectively to find similar patterns in sales from the other ...
53 views

### Is it still called linear separation with a layer of more than 1 neuron

A single neuron will be able to do linear separation. For example, XOR simulator network: ...
223 views

### How to make machine learning model that reports ambiguity of the input?

Suppose I want to build a neural network regression model that takes one input and return one output. Here's the training data: ...
34 views

### Solution to classify product names

I have a bunch of training data for classifying product names, around 30,000 samples. The task is to classify these product names into types of product, around 100 classes (single words). For example:...
67 views

### TensorFlow estimator DNNClassifier fails to fit simple data

The ready-to-use DNNClassifier in tf.estimator seems not able to fit these data: ...
240 views

### Does the correlation between inputs affect the model performance?

I'm currently working on a regression problem and I have 10 inputs/attributes. What should I do if there are correlations between different features of the input data? Does the correlation between ...
141 views

### How is regression machine learning?

In regression, in order to minimize an error function, a functional form of hypothesis $h$ must be decided upon, and it must be assumed (as far as I'm concerned) that $f$, the true mapping of instance ...
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### Can we compare MAE MSE results with categorical_crossentropy?

can i compare MAE and MSE loss results of a regression CNN with categorical_crossentropy loss of a classification CNN if they both have similar tasks? is yes how to?
28 views

### What Model Used for Forecasting Sales with Dynamic Holiday

I'm working on a project where I need to forecast sales data where I have history of 1 year (2017) daily data. I am new on Artificial Intelligence topic and after searching for a while, I think ARIMA ...
75 views

### Will LMS always be convex function? If yes, then why do we change it for neural networks?

In LMS(least mean square) since, we use a quadratic error function, and quadratic functions are generally parabola in (some convex like shape). I wonder whether that is the reason why we use least ...
93 views

### Understanding the math behind using maximum likelihood for linear regression

I understand both terms, linear regression and maximum likelihood, but, when it comes to the math, I am totally lost. So I am reading this article The Principle of Maximum Likelihood (by Suriyadeepan ...