# Questions tagged [linear-regression]

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

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### Linear regression: why is distance *squared* used as an error metric?

Usually when performing linear regression predictions and gradient descent, the measure of the level of error for a particular line will be measured by the sum of the squared-distance values. Why ...
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) ...
641 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 ...
273 views

### Regression on extreme values

I have a data set that looks like this: I would like to estimate a relationship between x-values and the corresponding 5% extreme y-values, something that might look like that : Do you have an idea ...
992 views

### How do you handle multiple categorical values in a single column for wide_deep model in tensorflow? [closed]

To start, let me just say that I am very new to tensorflow and Machine Learning in general. But, as part of my learning project I am trying to adapt the tensorflow wide and deep model to generate ...
231 views

### What makes a machine learning algorithm a low variance one or a high variance one?

Some examples of low-variance machine learning algorithms include linear regression, linear discriminant analysis, and logistic regression. Examples of high-variance machine learning algorithms ...
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 ...
2k views

### Matrix Dimension for Linear regression coefficients

While reading about least squares implementation for machine learning I came across this passage in the following two photos: Perhaps I’m misinterpreting the meaning of beta but if X^T has dimension ...
154 views

### Predict value from image set

I have a large dataset of skin images, each one associated with a hydration value (percentage). Now I'm looking into predicting the hydration value from an image. My thinking: train a CNN on the ...
156 views

### With gradient descent w/MSE on a regression, must/should every Epoch use the exact same training samples?

Let's say I've got a training sample set of 1 million records, which I pull batches of 100 from to train a basic regression model using gradient descent and MSE as a loss function. Assume test and ...
225 views

### How to implement Mean square error loss function in mini batch GD

I have a vectorized implementation of the neural network in c++. I successfully solve the classification problems of Fashion MNIST and CIFAR. Now I am modifying my code to do the Linear regression. I ...
67 views

### How exactly does a validation data-set work work in machine learning? [closed]

With typical machine learning you would usually use a training data-set to create a model of some kind, and a testing data-set to then test the newly created model. For something like linear ...
232 views

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

Is Deep Learning the repeated application of Linear Regression?
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 ...
136 views

### 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 ...
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 ...
237 views

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### 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 ...
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) ...
69 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 ...
95 views

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 ...
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 ...
62 views

### Do correlations matter when building neural networks?

I am new to working with neural networks. However, I have built some linear regression models in the past. My question is, is it worth looking for features with a correlation to my target variable as ...
31 views

### 3d representation of a regression with two independent variables one of them is categorical and another is continuous

I have hopefully a fundamental question of Do I understand things right. (Thank you in advance and sorry for my English which might be not so good) 1-Preambula 1: I know that if we have 2 independent ...
33 views

### What is the difference between an generalised estimating equation and a recurrent neural network?

What is the difference between a generalised estimating equation (GEE) model and a recurrent neural network (RNN) model, in terms of what these two models are doing? Apart from the differences in the ...
190 views

### Actor-critic algorithm using gaussian Radial Basis Function, Local Linear Regression and shallow Neural Network

I'm attempting to implement the actor-critic algorithm on Matlab using Radial Basis Function, Local Linear Regression, and shallow Neural Network for inverted pendulum system. the state space and the ...
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 ...
23 views

### Can number of Leads be predicted based on previous months

I have a sample set of data about Leads that gets generated every day. Leads are nothing but a user expressing request to be our partner or not. Sample data set is as shown below ...
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 ...
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:...
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 ...