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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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Right Cross Validation Implementation (Regression)

I am very new to machine learning and i am starting to work my way up. I have made an implementation for cross validation which will be used with ensemble models later. I have made a pipeline in ...
Guhan's user avatar
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Forecasting Resource Depletion in a Distributed System

I manage a distributed system where each node contains six interchangeable resource slots, sourced from a diverse pool of resource types. Each type has a finite number of units, which get consumed ...
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What do the terms in this equation $$θ_{1}x_{1}+θ_{2}x_{2}+θ_{0}=0$$ represent?

I am currently learning ML from a course by MIT. I am from a non tech background and unable to understand some equations shown in this lecture of Linear Classifiers: https://youtu.be/yOKDzd73KgM?t=57 ...
Steve's user avatar
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Model evaluation approach allowing manual experimentation without data leakage

In supervised machine learning, are there any evaluation approaches beside using a fixed holdout test dataset, which allow me as a scientist to manually compare preprocessing approaches, without ...
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Data binning for interval data

I am trying to create a ML model for salary classification into 5 categories (0-90k, 90-120k, 120-180k and so on). The problem is that in my dataset almost all salary data is presented in intervals. ...
pinkkdeerr's user avatar
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Custom loss function in python

I am trying to implement a custom loss function inspired by https://arxiv.org/pdf/2305.10464.pdf. That is: $ L(\mathbf{x}) = (1-y) \left\lVert \mathbf{x_{true} - \mathbf{x_{pred}}} \right\rVert^2 + y \...
Gst's user avatar
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How can i retrieve incorrect labelled predictions on new unseen data on image classification when i want to retrain my model later on?

I've recently made a binary image classification model with transfer learning. The model is used on an api and the predictions gets saved into a database. The problem is that it predicts images ...
Enes Aygun's user avatar
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How to derive at the expectation equation given in the paper "Video Diffusion Models"?

In the paper Video Diffusion Models, Section 3.1 mentions the following equation: $$ E_q[x^b|,z_t,x^a] = E_q[x^b|z_t] + (\frac{{\sigma}_t^2}{{\alpha}_t})\nabla_{z_t^b}\log q(x^a|z_t)$$, where $x^a, x^...
p1p13 's user avatar
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training data of stable cascade vs stable diffusion

So according to this: https://waxy.org/2022/08/exploring-12-million-of-the-images-used-to-train-stable-diffusions-image-generator/ Stable Diffusion was trained on data from CommonCrawler. I believe ...
x89's user avatar
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Question regarding model inference consistency

I am doing some research on gaze estimation model L2CS provided in here. When you look at the inference predictions on provided image, when face/eye direction barely changes, inference predictions ...
JohnDoe's user avatar
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How to train a recommender based on user_features, item_features and likes?

It is my first time dealing with recommender systems, so I don't understand which algorithm should I use. I am given dataset with columns "user_id", "item_id", "like" (0 ...
GulNkt's user avatar
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2 votes
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Text Classification with unlimited labels, Text Extraction?

I'm looking to use ML to read in a blob of text, and extract a name from that text blob. (The blob is from an OCR result from an iPhone) The text blob varies in size, but the name is always present in ...
Matthew Knippen's user avatar
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saving ML models with pickle to be deployed using Flask

I trained some ensemble Ml to predict, I needed to save with pickle so as to be able to deploy using Flask. To save with pickle I have tried several methods and read several articles but could not get ...
Kehinde Olatunji's user avatar
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Recreating results from Research Paper

so I have been trying to recreate the results from this particular paper (Neural Collaborative Filtering). The dataset I use closely resembles this . I understand that I should my data into train and ...
Panos_42's user avatar
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Why the f1 score on validation dataset significantly higher than f1 score on testing dataset?

I'm using a TensorFlow model that look likes this: ...
Furno's user avatar
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1 answer
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Struggling with normalization/Standardisation for machine learning dataset

Sorry for what is probably a very obvious/rookie question. I'm currently doing a data science module for my degree and making very slow progress with the work. The case study i'm doing is around HR ...
Alex Ferry's user avatar
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Build a Neural Network for Multi-output Regression

I have a network model that accepts about 25 inputs and outputs 3 actions. The outputs are: delta X and delta Y of the robot and the angle of the robot. After I enter the data into the model, I get ...
May's user avatar
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stabilityai/stable-cascade vs runwayml/stable-diffusion-v1-5

What are the major differences in these text-to-image AI models: stabilityai/stable-cascade runwayml/stable-diffusion-v1-5 in terms of architecture and performance?
x89's user avatar
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Model improvement

Whenever I try to solve some ML problem I get stuck on the first model I choose. I understand the bias-variance tradeoff, but I think it is not the only way to debug a model. Are there any tools to ...
DimitrijeCiric's user avatar
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Patterns in weights of trained model?

Apologies for a naive question. Let's say I am training a simple feed-forward neural network using stochastic gradient descent with a fixed architecture, learning rate, number of training epochs, and ...
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Variational AutoEncoder using a matrix as dataset with a time component or ...?

The project is to repair data/smoothing. I would like to use a matrix of shape (5,13,3922): 5 differents types 13 features, one of them is the Times series, dates in format yyyy-mm-dd that I turned ...
Adurrow's user avatar
2 votes
1 answer
46 views

Autoencoders are fitting anomalies too good

I have a set of ~ 5000 greyscale images with resolution of 64x128. I want to do an unsupervised anomaly detection. As a first try, I chose convolutional autoencoders (AE) and trained an AE model. I ...
vinodh_eee's user avatar
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What are tools and lesson do I need to make an AI drone?

Recently, I've been exploring AI drones online, and I've conceptualized an exciting idea: creating an advanced automated AI drone. This drone would be capable of flight controlled through text ...
user162294's user avatar
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When is sampling bias acceptable?

Overview: Dataset is small and a bit messy and the task is to classify 5 classes wherein the targets are ordinal. Feature Engineering and Selection, Model Tuning, etc. did not produce acceptable ...
easymoneysniper's user avatar
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1 answer
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How can a citation dataset (like Cora) have strongly connected components?

This website https://snap.stanford.edu/data/cit-HepPh.html shows that the High-energy physics citation network has strongly connected components and it's driving me crazy. A SCC would mean that you ...
StackExchanger's user avatar
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Extremely Imbalanced and Gapped Dataset in Regression Problem

Currently I am working with a biological dataset with a range of 0-to-1 to do a multi-task regression with Deep Learning. However, this dataset has an empty gap in the range 0 to 0.2 (however there ...
Abdullah Faqih's user avatar
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Is balancing imbalanced validation set for retraining model after hyperparameter tuning required?

The following are basic steps to modelling, but would like to ask in the case of imbalanced data, is balancing of train dataset required when retraining model on train + validation set after ...
curious-24-7's user avatar
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Is GroupKFold needed if some samples have some of their feature values equal?

I am given a dataset $D$ of 10k enzyme-substrate complexes having a lock-key relationship, with each sample (complex) being characterized by enzyme features $x_e$ and substrate features $x_s$. That is,...
ado sar's user avatar
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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
1 vote
1 answer
20 views

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 ...
nOhAr's user avatar
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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
1 vote
1 answer
15 views

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
1 vote
1 answer
27 views

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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30 views

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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6 views

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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12 views

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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57 views

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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18 views

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
1 vote
1 answer
54 views

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
1 vote
1 answer
80 views

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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10 views

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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8 views

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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1 vote
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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 ...
umbe1987's user avatar
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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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1 answer
21 views

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
1 vote
1 answer
48 views

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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23 views

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