Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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Integration of the sum of gaussians over a line

suppose we have two independent gaussian distributions $X$ and $Y$ . let $Z = X+Y$ which will be a gaussian too. the goal is to compute : $ \int_{L} X+Y=c $ Where L is the line : $X+Y=c$. My professor ...
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optimization of solving an equation with machine learning

I would like to optimize the computational time of a self-consistent equation resolution. Basically, the idea is to generate data of the convergence of a value that I just can obtain numerically ...
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Two confusion matrices

In a machine learning context, I am working on a binary classification problem. There is a source of truth $T$ for labels, and a labeling process $A$ which is not perfect and makes errors compared to $...
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How do I check that I need to make different models for two different datasets belonging to same equipment installed in two different power plants? [closed]

What method can be used to check whether I need to build a single model or different models if the data is coming from the same equipments installed on different sites where conditions can be ...
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Propensity of customer to buy a new product?

I am tasked with deciding whether a new product should be developed. I have data of customer transactions of previous products and wish to build a model which determines whether customers will have a ...
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how does `subsample` parameter work in boosting algorithms like xgboost and lightgbm?

From what I know, both of them are sequential learners and only the 1st tree in the sequence gets built on the data and all the following trees that get built are to correct the mistakes of previous ...
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How to forecast a Macro trend by multiple Index time-series Using LSTM Model?

I am new in machine learning and I found that lots of article only train the LSTM model by only one stock and do the forecast. ...
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Predicting estimated time of arrival (ETA) with custom loss function

I have an assignment of ETA prediction that I'd like to seek some advice from you. I need to train a model from a dataset to predict ETA of parcels as dependent variable, which is discrete (in days). ...
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Is it possible to use attention in non sequential data in neural networks?

I'm still trying to understand the attention mechanism. It is not clear to me what query, key, and value mean yet, for example. However, my main issue is regarding how to apply attention in my use ...
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How to train LSTM model with multiple index futures to forecast marco economy trend? [duplicate]

I want to try predicting the macro economy trend by grouping different index futures. I have came up 2 approaches and listed below. May I ask what is the right approach for handling multiple ...
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Why not link features instead of selecting them - Clustering

Currently, I am working on customer segmentation using their purchase data. I plan to use clustering techniques. So, my data has below info for each customer (9 features and 1 id field) Now I am ...
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How to perform image classification in a dataset of images with heterogeneous sizes?

I have a dataset of images with very different sizes (ranging from 100X100 pixels to 5000X1000 pixels) and aspect ratios. I want to use neural networks for dealing with this problem. Is there any ...
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Most Random Forest Features are the same

I have a random forest with let's say 256 trees and say 2000 features. from data processing to actual prediction, it takes several hundred microseconds, I was wondering if there were any ways I could ...
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I have troubles with getting a neural network to learn a function [duplicate]

I am currently trying to make an artificial neural network learn a function that takes a 1 dimensional input and the output is also of dimension 1. However, I have some troubles making the network ...
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Meaningful to retrieve original value after standardization using clustering

I already referred these posts here and here. Currently, I am working on customer segmentation using their purchase data. So, my data has below info for each customer Based on the above linked posts ...
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How to derive solution to loss function of GLasso for precision matrix

I am trying to find the parameter $\hat\omega = min_{\omega}\Big(-log|\omega| + tr(S\omega) + \sum_{i,j}\lambda|\omega_{ij}|\Big)$ This is to regularize the precision matrix $\omega$ for the GLasso. ...
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How to cluster binary data using excel or pandas dataframes? [closed]

I have a CSV with 101 rows and 150 columns. I need to find a way to segment/cluster the ID's using the Column values. It can be a machine learning approach or just using Excel techniques. At the end ...
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Under what circumstances is a m-class classification Neural Network equal to a base category logit model for nominal responses

Here is the setup for an m-class classification neural network. $$z_j=\sigma(\alpha_0j+\alpha_j^T x), (j=1,...,k)$$ $$t=\beta_0+\Sigma^k_{j=1}\beta_j z_j)=\beta_0+\beta^Tx, (l=1,...,m)$$ $$ y=f(x)=g(t)...
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Yolo Algorithm for custom object detection with Multiclasses

I am building a project to detect waste such as plsticbottle, plastic bag, mouse, keyboard and clothes. I have created a dataset and annotated it using labelimg. From the labelled images I have ...
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what if range of normalized of data in machine learning goes beyond?

Normalization in machine learning is the process of translating data into the range 0 -> 1 or -1 -> 1. What if the values goes above 1 or below -1. What does that mean? Is it again an outlier? ...
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MLE for Two component mixture model

Chapter 8 section 8.5.1 of the Elements of Statistical Learning book describes a simple mixture model for density estimation and the associated EM algorithm for carrying out maximum likelihood ...
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How XGBoost chooses between two features that gives the same information?

I have 10 variables in a dataset (X1, X2, .., X10) plus the binary target variable (...
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Correlation between variables from a XGBoost lens?

I have 10 variables in a dataset (X1, X2, .., X10) plus the binary target variable (...
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How to know if two variables with similar feature importance are replaceable in XGBoost?

I have 10 variables in a dataset (X1, X2, .., X10) plus the binary target variable (...
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Coefficient of correlation between differently spaced time series

I have a timeseries with input flow values in a water plant (measured every 5 minutes) and the meteorological data containing the precipitation in the last 1,3,6,12 and 24 hours (each displayed every ...
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The multivariate Inverse-Gamma

On wikipedia they give a multivariate form, which to my understanding is used when V is known up until the scaling factor for a Normal-InverseGamma conjugacy. I tried to find a source of the ...
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Selecting a test to prove that the observed changes in the performance of two machine learning models are statistically significant

I have developed two machine learning models which I evaluated with two different datasets. My initial hypothesis was that their performance would be higher in dataset 2 as compared to dataset 1. ...
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Without encoding, how can we solve high cardinality issue?

I already referred the posts here but this question is different. I don't wish to use categorical encoding. details given below I have a dataset of 3000 unique customers purchase data. The dataset ...
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Temperature Lag calculation

I am working on a data science project on an industrial machine. This machine has two heating infrastructures. (fuel and electricity). It uses these two heatings at the same time, and I am trying ...
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Help with terminology & methodology for a hierarchical (& imbalanced) classification problem

I have a dataset that I am not sure how to analyze, or at least I am not sure of the terms to read up on. I have 25 groups. Each group belongs to one of 3 locations. Each group consists of multiple ...
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For a CNN Neural Network, why do we need to specify the number of nodes in the Conv2D function in Keras? [closed]

As I understand, in CNN, we are only doing dot product calculation on the image in the convolution layer. Below is an example of convolution code. ...
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Calculating Shannon Information of Data Augmentation Strategies

I recently caught Andrew Ng's 2021 talk on MLOps (MLOps: From Model-centric to Data-centric AI). At 26:40, he talks about calculating the effectiveness of cleaning your data (training examples) vs. ...
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Neural networks - what is the point of having sigmoid activation function $\sigma(.)$ AND sigmoid g(t)?

Just so we're all on the same page, this is the classic neural network set up as I understand it: $$z_j=\sigma(\alpha_0j+\alpha_j^T x)$$ $$t=\beta_0+\Sigma^k_{j=1}\beta_j z_j)=\beta_0+\beta^Tx $$ $$ y=...
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Using Variance of time series as input feature for time series clustering

I have a time series dataset, it is a data frame with 2000 rows and 1000 columns. Each rows is for one specific id and has a unique pattern. I want to clustering this data into multiple classes. Let ...
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Hyper parameters to tune in Bayesian network?

In tree based models and neural networks, we can optimised the models by tuning the hyper parameters(such as: learning rate, number of neutrons.. etc). Is there a hyper parameters to tune in Bayesian ...
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RFM Customer segmentation - Why Avg monetary value instead of total monetary value?

I am trying to segment our customers based on their purchase data. And I came to know about the RFM technique (Recency, Frequency and Monetary) through these posts here, here etc. Recency - How ...
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Modeling demand distribution with selling constrained by stock

I'm working as a Data Scientist on a project where we are supposed to determine how many pieces of stock a certain retailer should have in each of its physical stores. The stock should be set on the ...
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1 vote
1 answer
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Can I convert a typical reinforcement learning problem to a supervised learning problem?

I'm not sure if I've understood correctly the whole point of reinforcement learning. In my point of view, the whole goal of RL is learning a policy that maps states to actions. Let us suppose that I ...
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How does attention add expressive power to encoder-decoders?

I am learning about the attention mechanism for the first time, and the context in which it has been introduced (watching Lecture 8 of Stanford's CS224N) is that of language translation using seq2seq ...
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Multiclass classification on top of given probability distribution from previous model

I have a multiclass classification problem that has multiple steps. Firstly, I am given a probability distribution over the classes by a base model for each sample. The task is to create a new model ...
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1 vote
1 answer
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Neural networks - calculating output manually if $x_1=x_2=0$ . Should this be easy to do?

This is a problem question I'm trying to make sure I understand from a past paper (with no solutions). The R output is below. ...
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Interpreting Shapley Values on Breast Cancer

I was analyzing Shapley Values on the Wisconsin breast cancer data set (binary classification). I applied it on Random Forest and on Ridge and Lasso Regression. However the summary plot seems to be ...
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2 votes
1 answer
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1D cluster - Jenks optimization - Finding optimal number

I have a sample data variable shown below score 10, 11, 12, 90, 95, 97, 38, 37, 35 Instead of applying/binning data based on ...
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Assessing importance of interactions between categorical features

The issues with using feature_importance of models such as XGBoost, or even using packages like SHAP or ELI5, is that the results are displayed in a way that doesn'...
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Does using grid search for hyperparemeters make test set redundant?

The purpose of train, validate and test data splits addresses the issue of data leakage when tuning for the model's hyperparameters. Does Grid Search then eliminates the need for test set? Because ...
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"Consensus" on Analyzing Mixed Continuous and Categorical Data in the field of Statistics? [closed]

I have been trying to determine the popular "consensus" as to how mixed continuous and categorical data (e.g. a dataset that has variables on income and gender) is generally analyzed in the ...
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How can I train Mixture Density Neural Network? [closed]

I am learning Mixture Density Neural Network but it looks different from the usual neural network for regression problem. As far as I have understood from what I have read on the Internet, it gives ...
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Implementing kernel alignment for SVM algorithms

I am trying to understand and re-implement the results from Table 2 in the first Kernel-Target Alignment paper. The task that is being done is a simple classification task using an SVM with RBF ...
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How do you approach a CNN problem?

I wanna create a machine learning model based on a region based CNN architecture (either RCNN, Fast RCNN or Faster RCNN). As an framework I wanna use Pytorch. I made a image containing apples and ...
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2 votes
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How to manage out of sample data in the long run?

For example, you are interested in testing an investment strategy and there is data from 1950 to 2022. So you split it into a train and test set, say 1950-2000 and 2000-2022. Then you build your model ...
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