Questions tagged [machine-learning]

Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.

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Clean CSV file using ML

I would like to build a Neural Network to clean a CSV file that contains wrong delimeters. My approach is the following: Identify rows that have more columns than the header. Define these rows as &...
DoktorMLNoob's user avatar
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Need inputs on logging Machine Learning models and their versions in logs for my application

So i have a web application that recommends movies based on the subject and question that the user puts in , it also uses NLP and ML models like Named Entity Recognition(NER) model to extract keywords ...
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Adaptive Lasso Coefficient Weights

I'm trying to understand how the Adaptive part of Adaptive Lasso works. I understand that theoretically, the weights for zero coefficients are inflated to infinity. But can someone explain this ...
user162172's user avatar
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Why do we use only event history as input for temporal point processes?

I'm trying to understand temporal points processes. In particular, neural TPPs. In all the works I've read, the only features fed into the model are a sequence of event timestamps and marks if they ...
JulioHC00's user avatar
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Call volume prediction using LSTM and GRU

Machine Learning call volume prediction using LSTM and GRU I am trying to predict the number of incoming calls using LSTM and GRU I have done all the data preprocessing but upon training the model I ...
Kuda Kulrider's user avatar
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Best modelling method when target is a distribution

I have a regression task where each data sample is annotated by multiple (5-10) experts. I observe that the annotated target of each data sample is a Gaussian distribution. Usually, people will use ...
zqtan98's user avatar
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Question about the limitations of regularization

I am training a neural network which is overfitting. Even when I increase the number of parameters, the test lost plateaus while the training loss keeps decreasing. Can regularization (like an L1 or ...
vermillion flycatcher's user avatar
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Multilabel Classification - Flat Binary Classifiers vs Hierarchical Binary Classifiers

Was researching on multi label classification to solve the problem of tagging news articles with topics and countries, where tags follow the syntax <topic>-<country>, and would like to ...
curious-24-7's user avatar
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I am training LSTM model for flood water level prediction. How to make the performance of the model better?

...
Param Thakkar VJTI CS's user avatar
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How to Identify Equipment Churn from Laboratory Service Records Without Direct Churn Labels?

I'm analyzing a dataset encompassing 20 years of laboratory equipment service records, which includes the equipment ID, service dates, types of equipment (HOOD_TYPE), and descriptions of performed ...
tlengman's user avatar
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Resources for writing CNN for semantic segmentation

I am intermediate/advanced in Python and new to machine learning. Most of what I know about deep learning I learned through Deep Learning with Python by François Chollet. I am trying to do image ...
utx7563yu's user avatar
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How can I combine/pool of the results of regression with neural network?

My study has ten imputed dependent variables (plausible values). After separately analyzing each dependent variable using a regression neural network (NN), I must combine/pool the results. I tried ...
minre's user avatar
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How to compute confidence interval xgboost regressor?

I have time series data to predict values for the next 6 months. I have an xgboost model that predicts the six individual months, for the business what is important is that the cumulative value of ...
tailsrockc's user avatar
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Invertible neural network 1 input/output but higher dimensionnal hidden layers

I want to create an Invertible Neural Network that has 1 input, it expands into hidden layers with multiple neurons and ends with 1 output. The constraints are, my neural network will have strictly ...
Emmanuel Andre's user avatar
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Evaluate KNN in recommender system

I'm a newbie in machine learning and I'm currently have a project about building a collaborative filtering (user-based) product recommendation system using KNN. My data has no label, it consists of ...
Arkadian's user avatar
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What's wrong with my implementation of an MLP?

I'm trying to predict housing prices from a Kaggle dataset using an MLP with 3 hidden layers (10 neurons each). Having read about MLPs and backprop in the CS229 notes, I tried to do my own ...
The_Monetarist's user avatar
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ML Project Question - Non-deterministic cost function

I'm hoping to run a ML gradient descent analysis to help tune a multi step non-deterministic simulation with 15 or so parameters. The simulation function is non-deterministic because it contains a lot ...
KC Pruitt's user avatar
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Combing Output of Two Regression Models

I have two models. Model 1: I have a dataset of American high school students and their test scores and other characteristics. I built an ARDRegression model that predicts how well a student will ...
Mary's user avatar
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Uncertainty in stacked ensemble model

I am using the stacked generalization scheme to combine the predictions from different machine learning models (input models from now on). I am currently calculating the prediction interval for each ...
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LSTM, different size for feature set and target

I am trying to build a weather forecasting model. X_train shape :(2970, 1, 9) Y_train shape : (3299675, 1, 4) I am following ...
Abhishek Patil's user avatar
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Why are some columns of feature matrix after dimentionality reduction zero?

I am trying to implement a paper in which the ultimate goal is to predict mutliple labels for instances (which are genes here). The feature matrix with shape of 1236*18930 is built by calculating term ...
Satarnejad's user avatar
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How to Balance Dataset extracted using image_dataset_from_directory

I'm new to tensorflow, so I've been trying to find the best way to do class balancing over a dataset where I used image_dataset_from_directory to load. But I haven't find the way to do it. I saw from ...
lopez-mgu's user avatar
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Validation loss not decreasing

I am building a model for predicting stock portfolio positions, by minimizing a Sharpe loss function (corresponding to maximize the Sharpe ratio of the portfolio). The architecture is puting ...
Dan Lee's user avatar
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1 answer
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Сan we say that the regression problem is essentially a classification problem with an infinite number of classes?

I'm a newcomer to machine learning and currently diving into supervised learning methods. I've already grasped the theoretical basics of classification tasks and have just started exploring regression....
SuperciliousMe's user avatar
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How to combine a classificiation dataset with a pair-wise comparison dataset

Let's say I'm trying to train a neural network that predicts a single output [0.0, 1.0] value that correlates to photo realism which I can use either in a classification setting or for ranking. I have ...
ahbutfore's user avatar
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Change of data shape when using IterativeImputer from sklearn

I am using the IterativeImputer from sklearn and I notice that it changes the data shape. Initially I have an (X,5) array where all columns except for the last one contain the missing value (which has ...
gmaravel's user avatar
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How to interpret annotation data?

I am new to datasets. I have got an annotations train.json for MR image data like this - I want to train a Yolo-V8 model using this MR data images extracted from dicom raw data and annotations for ...
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Can we calculate Bayes Error rate, if we have a simulated data?

I am going through ISL(Python) and in section 2.2.3 ( Page No. 36), the author writes, "For our simulated data, the Bayes error is 0.133. It is greater than zero, because the classes overlap in ...
Prashant Kumar's user avatar
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Understanding batching in pytorch models

I have following model which forms one of the step in my overall model pipeline: ...
Mahesha999's user avatar
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Calculation of Covariance Matrices for a QDA classifier in Python Numpy

For a school project, I have to design a QDA classifier for 28x28 pixel images of letters in sign language. I have been given 27455 images for training, which have to be flattened to a 784 pixel ...
Neev Penkar's user avatar
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Machine learning model that takes multiple records as input to help predict the last

I want to create a ML model that is able to forecast the yield from a farm. My data source gives me data about the inspections from the field, but that is too much info to fit in 1 record, so there ...
Milan N's user avatar
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Feature Selection in no labeled data

I'm new to this field and trying to learn by working with a fraud dataset. Initially, I used the dataset as is, but now I'm trying unsupervised learning without the labels. I've tried clustering ...
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Class imbalance problem in binary classification of ecg and eeg data. I am cross posting it here from stackExchange as per a user suggestion

I have attached the link to the stack overflow question page under. In short it is a Class imbalance problem in binary classification of ecg and eeg data. https://stackoverflow.com/questions/78232398/...
Shanthanu's user avatar
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Best value of K when using K-Nearest Neighbors with Spectral Clustering

I'm using scikit-learn's SpectralClustering class, which has the option of building its affinity matrix using a K-Nearest Neighbors algorithm. Is there any way to ...
Hippopotoman's user avatar
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Combining monte carlo with deep learning to improve the estimation

I am in situation where i need to estimate the attenuation of an EM wave . we consider EM wave as collection of photons. These photons when strike with some dust particles they scatter in different ...
user7341333's user avatar
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Lost when trying to get good time series prediction results (regression problem) even after trying many things

I'm not able to get good results after a long time testing when using TensorFlow to predict time series data (regression problem). I don't know if the problem is with the data (little quantity and/or ...
Marco's user avatar
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VC dimension of a class H that assigns 1 to at most k points or that assigns 0 to at most k points

Let X be a finite domain and k a number such that k≤|X|. Consider the hypothesis class H:={h:|{x∈X:h(x)=1}|<=k or |{x∈X:h(x)=0}|<=k}. Find VC dimension of H.
Harsh Choudhary's user avatar
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Doing correctly paired-trial validation

In paired-trial validation, a statistical (ML) models are trained on $n$ datasets separately and then applied to other datasets, as a way of estimating the generalization of the models obtained. ...
Roger V.'s user avatar
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Dataset for access control policies?

I'm working on a dynamic access control policy generation model using machine learning and I need a real dataset to evaluate the performance. Is there any access control policy dataset consisting ...
Binod Karunanayake's user avatar
2 votes
1 answer
80 views

How to do a Multilabel classification where the label order is important?

I am new to machine learning and I hope I used the right term in the question. So I am doing carbon composite modelling for my college project, and each composite sample are created by stacking ...
apotheke's user avatar
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When applying softmax over multiple dimensions of a tensor, does the order in which those dimensions are matter?

Lets say i have a tensor of order 256, dimensions indexed from 0 to 255. Lets say i am writing a function implementing the softmax operation because i am a newbie and i want to understand the ...
Maciej's user avatar
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Trying to train a denoising autoencoder to restore missing information from a binary image

I am building a denoising autoencoder to repaint lanes from a binary image. The input is a binary image that has incomplete lanes, due to vehicles getting in the way. I repaint the lanes manually so ...
Kaif Ibrahim's user avatar
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Question on theory from original GBM article

I am reading the original gradient boosting machine article and, maybe because my statistics are a bit rusty, have a few questions on one section. In section ...
CarterKF's user avatar
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Understanding the code for calculating the 95% confidence interval of AUC using bootstrapping

It's really embarrassing, but I lack statistical knowledge. I would like to find the confidence interval for AUC at 95%. Actually, I got the code from here(https://stackoverflow.com/questions/52373318/...
JAE's user avatar
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input problems of using LSTM in python to forecast future value

There are two columns rainfall data and water level in my dataset and I want to predict the water level based of the past values using LSTM on python. My problem is do I need to include the past ...
user161683's user avatar
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How to predict inside of the box temperature at a give outside temperature using python?

I Need help predicting inside of the box temperature at a given outside temperature. Background I have a system (also known as a BOX). The BOX is insulated from the outside environment and contains ...
Dennis's user avatar
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Question about contextual embeddings?

How do BERT and RoBERTa generate contextual embeddings? The articles I've read keep saying that transformer encoders work bidirectionally. Because of self-attention, they can look at every token, ...
abcd's user avatar
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Stream response from custom RASA actions to the chatbot

I am using RASA PRO with CALM. I was thinking of using openai api within a custom action and stream the streaming response coming from openai to my chatbot. Openai is giving me streaming response and ...
Avatar's user avatar
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graph neural networks for molecular embeddings

I want to extract the embeddings from various graph neural network designed for small molecules. I want to know does the model need to be trained to do the same. Or should be extract the layer in ...
As13's user avatar
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Training split generation - Extremely Slow

I am fine-tuning mbert on wikipedia dataset, loaded with Datasets (Hugging face) ...
GaiusGhislerianus's user avatar

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