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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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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
1 vote
0 answers
10 views

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
1 vote
0 answers
17 views

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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0 answers
25 views

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
0 votes
1 answer
37 views

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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0 answers
5 views

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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19 views

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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0 answers
9 views

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 ...
user101010's user avatar
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0 answers
5 views

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
36 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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0 answers
21 views

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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0 answers
45 views

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
1 vote
1 answer
25 views

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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0 answers
27 views

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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0 answers
22 views

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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5 views

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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0 answers
15 views

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
18 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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0 votes
0 answers
23 views

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
14 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
26 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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0 votes
0 answers
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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
0 votes
0 answers
29 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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0 answers
11 views

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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0 answers
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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0 answers
8 views

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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0 answers
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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0 answers
23 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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0 answers
17 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
43 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
50 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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0 answers
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
0 votes
0 answers
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
0 answers
25 views

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
  • 111
0 votes
0 answers
12 views

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
0 votes
1 answer
20 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
26 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
0 votes
0 answers
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
1 vote
1 answer
38 views

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
0 votes
0 answers
14 views

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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1 vote
1 answer
20 views

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
  • 111
0 votes
1 answer
27 views

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 ...
mrin9san's user avatar
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0 votes
0 answers
9 views

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
0 votes
1 answer
14 views

Understanding batching in pytorch models

I have following model which forms one of the step in my overall model pipeline: ...
Mahesha999's user avatar
0 votes
0 answers
18 views

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
0 votes
0 answers
22 views

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
0 votes
0 answers
8 views

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 ...
DrGenius's user avatar
  • 101
0 votes
1 answer
17 views

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
0 votes
0 answers
12 views

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