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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CGAN not getting conditioned properly. How to start debugging?

So I was trying to condition some images (10 classes) on corresponding EEG signals. However after traing, the CGAN is producing decent looking images but the images being produced simply do not ...
Maurya's user avatar
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Handwritten text to digital versions - software, libraries, options

What types of (presumably machine learning) software/libraries exist for taking handwritten text in tables into a digital format? The tables may not always be the same. So I assume it might be fairly ...
Socorro's user avatar
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Image Classification when image is a plot of two functions

My goal is to perform a supervised classification of a number of objects. Each object is described by a plot of two functions, f(t) and g(t). The plot dimensions, (b - a) and T, are about the same ...
James's user avatar
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How to Determine the Minimum Value of a Continuous Variable for Predicting Categorical variable using Logistic Regression?

I am using logistic regression to predict df['MortSubiteCardiaque'], which contains 0 and 1, based on my continuous variable df['NTProBNP']. I would like to determine the threshold for df['NTProBNP'], ...
Mohamed kenani's user avatar
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How to determine the optimal number of trees in Random Forest?

Here I list possible answers for mine: Do you use the graph for OOB? Do you use any other kind of graph? Do you take a fixed number in default? Do you take in consideration any research paper ...
Anisa's user avatar
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K means clustering of image with k=1 vs mean of all pixels

I have relatively uniformly colored images and I extracted colors using k-means. k means 1 showed the best results for my modeling purposes, k means 2 not so much, and with k-means 3 there ceased to ...
phil27's user avatar
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1 answer
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When would pandas.get_dummies()'s parameter of drop_first=False be appropriate to use?

While working on some case studies that use various machine learning models, I came across a project for predicting churn in the telecom industry. The Jupyter Notebook I saw had the following lines of ...
Rakesh Poluri's user avatar
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1 answer
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Is it possible to have different amount of features for the Classification decision in a support vector machine?

Is it possible to train a support vector machine with two classes using two features and then trying to make a decision for a new data object to which class it belongs that has the same two features ...
Johannes's user avatar
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65 views

Questions about hidden states of bidirectional LSTMs

I read this in an article about bidirectional LSTM: In bidirectional LSTM, each word corresponds to two hidden states, one for each direction. Thus, we concatenate these two hidden states to ...
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Information retrieval SOTA models

Where can I find sota models of information retrieval? My task is to rank documents by given query by semantic search of embedding. I know that models like ColBERT, SPLADE solve this problem, but I ...
prostak's user avatar
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What's the best model choice for a non-linear regression task?

I have a dataset with the following format: Rows: 3700, float_columns: 17, int_columns: 2, categorical_columns: 12 Target Type: Continous, float My dataset is an insurance dataset that stores the ...
Connor's user avatar
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How to Yield a Better AUC / Lift Score?

I have a dataset with 200k records and 173 features focused on binary classification. Class proportion is around 98.7:1.3 (1.3% target=1). Currently, I am trying to increase the performance of my ...
DM_FCP's user avatar
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3 votes
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How to deal with a dataset in which categorical features have one value for specific class?

I have a multiclass problem and for the class equal to 2 in the target I have some categorical columns with just one value. For instance, is like for the observatuons with the target equal to 2, the ...
Aldla E Aoepql's user avatar
1 vote
1 answer
120 views

Is vision transformer (ViT) always better than CNN?

The paper - AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE proposed vision transformer and outperformed CNN-based models in many cases. When it comes to sequential data, we ...
Chuck Liu's user avatar
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Performance difference between two equivalent ML codes

Using the two Python libraries GPyTorch and scikit-learn to perform Gaussian Process Regression (GPR) for a machine learning task, I have encountered a problem I failed to solve during the last days. ...
C_Swann22's user avatar
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What are the differences between BPE and byte-level BPE?

In Roberta, I'm not sure if the model use BPE or byte-level BPE tokenization, are these techniques different or the same ? Can someone explain ? Thanks
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What is the complexity of ICE (Individual conditional expectation) on ensemble trees

I'm evaluating different model-agnostic methods on gradient boosting or random forest model. For Shapley, specifically TreeSHAP, the complexity is O(TLD^2) according to Lundberg et al. 2018. T: #trees,...
wealthh2's user avatar
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How do I shape my output data for a time series classification problem using LSTM

I am wanting to use an LSTM for anomaly detection on a multivariate time series data. Let's say there are n rows each corresponding to a timestamp incrementing by an hour and d input features and d ...
Vjs's user avatar
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1 vote
2 answers
180 views

Kernel Kmeans formula

I'm trying to implement the Kernel Kmeans algorithm but I struggle with the following formula : Let's say I have a case in one dimension with three points : 1, 5, 9. Let's say I want two clusters. ...
app_idea54's user avatar
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Which dataset could be a good choice to train Environment Sound Classification model for user environment awareness while wearing earbus?

Which dataset could be a good choice to train an Environment Sound Classification model for the following use case: use the model in the earbuds/earphones to detect important sound events in the user'...
Danijel's user avatar
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1 answer
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How can I predict the best treatment to give to new patient?

As part of a school project, I have to analyze a dataset with patients (with characteristics: sex, age, smoker 0/1, etc.) who received different treatments (one per patient) with a response to this ...
lea's user avatar
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Fine tuning LayoutLMv2 For Token Classification on CORD dataset

I use this colab: https://colab.research.google.com/drive/1AXh3G3-VmbMWlwbSvesVIurzNlcezTce?usp=sharing to Fine tuning LayoutLMv2ForTokenClassification on CORD dataset here is the result: https://...
Elia Weiss's user avatar
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Sale Forecasting Problem -- Is it legit to use inventory level as a feature?

I'm working on a project to predict future sales for our company's products so that the supply chain can have better idea how much to restock. Detail about the model I'm working on: Model: LGBM (from ...
user159479's user avatar
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What feature selection method is best for a multi class classification problem with one-hot-encoded columns?

I am trying to solve a multi-class classification involving prediction the outcome of a football match (target variable = Win, Lose or Draw). With a dataset of 2280 rows, which is 6 seasons of ...
pastybake2002's user avatar
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Help with a MaNet finetuning (binary semantic segmentation task)

Introduction: I am currently working on a computer vision problem, I have satellite images and I have to detect a particular archeological structure (Tell). I have access to the previously made ...
Alessandro Pistola's user avatar
2 votes
2 answers
82 views

Improve text classification accuracy

Task: I am building a text classification for salary prediction for data science jobs. I want to achieve at least 70 percent accuracy. Data: Features: Consists of job descriptions of data science, ...
Sendhan's user avatar
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0 answers
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How to find the minimum data point that predicts the target class in longitudinal data

I am working on medical data where a screening is done regularly for 200 days. I need to know the minimum number of screenings that can predict the outcome. I also need to know the best time/times to ...
Ghof-90's user avatar
2 votes
1 answer
88 views

What is the difference between hidden states in RNN and Transformers model?

I'm very terrible at NLP and I have searched for these questions but didn't find any answer, my question is, in RNNs, there are hidden states to remember information for processing the next state, and ...
user avatar
1 vote
1 answer
81 views

I dont understand this way of having a stable train/test split even after updating the dataset

...
samsamradas's user avatar
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2 answers
27 views

Using a Genetic Algorithm in junction with a digit classifier CNN to create an "MNIST image generator"

I'm trying to use a genetic algorithm that optimizes a 28x28 matrix (its shape) to make it look like an image of the number 7 that could be found in the MNIST image dataset. My attempt is to basically ...
kal_elk122's user avatar
1 vote
0 answers
50 views

Bad metrics results by strong class imbalance in Credit card classification

Hi i'm currently in the process of writing my bachelor's thesis and stuck at a some steps. I've developed a few ML-Model (XGBoost, (Balanced) Random Forest, ElasticNet,...) on an extreme imbalanced ...
user159373's user avatar
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0 answers
8 views

Is it fair to say that Hausdorff Distance (HD) focuses on low level details while dice score (DSC) high level

I wonder if its make sense to say that Hausdorff Distance (HD) measures low-level details while dice score (DSC) focuses on high levels. If you could cite a paper, I would appreciate it.
user836026's user avatar
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1 answer
43 views

Is Maximum Mean Discrepancy (MMD) suitable for comparing distributions with different sample sizes?

I'm working on a project where I need to compare the similarity of two probability distributions using MMD. However, the two datasets have different sample sizes. I've read that MMD can be affected by ...
Adham Enaya's user avatar
1 vote
1 answer
37 views

Nearest neighbor method for class identification problem

I have training data that consists of dates and times of different people entering the building. Test data consists of dates and times and their pseudonyms instead of their real names. I need to ...
Nick The Dick's user avatar
1 vote
2 answers
130 views

Seeking Guidance on Constrained Input Modeling for Soil Moisture Correction Using Rainfall Observations

I find myself immersed in the intricacies of working with 2D modeled fields (images) representing soil moisture in regions where direct observations are unfortunately absent. However, there is a ...
Seyed Omid Nabavi's user avatar
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0 answers
16 views

Is it possible to calculate a GRU RNN in its entirety by hand on a small dataset?

I want to see whether my code works and compare it to the results I do myself
J_Bake's user avatar
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0 votes
1 answer
93 views

Kernel Kmeans implementation

I'm currently trying to implement the Kernel Kmeans from scratch. At the time I'm writing this post, my implementation is perfectly working on nested circles dataset or even on Iris dataset (see ...
app_idea54's user avatar
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0 answers
28 views

Why is it bad for neural networks to output indices?

Let's say you wanted to train a neural network to output N indices (maybe it's sorting an array). There are at least 2 possible ways one might sample from this ...
Foobar's user avatar
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19 views

Is using Probability Classification to predict whether a restaurant will purchase the best approach?

I have a data set that contains data about restaurants in the United states including menu, foot traffic, type of cuisine, type of restaurant, and other restaurant attributes. I also have a small ...
erich's user avatar
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0 answers
12 views

Using two different dataset file formats to train model

I am looking to train a model on computer vision for imsge prediction but I have an images dataset and a .csv dataset. Note: both datasets have 6 classes A, B, C, D, E, F, only different is the file ...
37307554's user avatar
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0 answers
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Dataset with replicates: aggregation or not?

I am currently developing a neural network tailored to a regression problem using a synthetic dataset derived from an experimental simulation campaign. Given the stochastic nature of both the ...
Andrea Ferrari's user avatar
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0 answers
45 views

Heavy right skewed target

I scrapped Data science job postings of almost 1000 jobs for salary prediction. I wanted to bin the salary column and build a classification model from the job descriptions. But the (salary)target is ...
Sendhan's user avatar
  • 21
0 votes
0 answers
25 views

CNN segmentation models: class weights specification on IoU metric

I am building a MANet model using pytorch lightning. For getting the model I use the library segmentation models. As my objective is to do binary semantic segmentation, during the test phase I ...
Alessandro Pistola's user avatar
1 vote
1 answer
42 views

text extraction from bank statements from pdf format

I have bank statement memos containing transaction tables I need to extract. I only need to extract the transactions list. I have tried to use the Amazon text extractor, LayoutLM but since every bank ...
Abduhoshim's user avatar
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0 answers
11 views

10-Year SDET Looking to Pivot to ML - Seeking Advice and Insights

I'm on a journey to pivot my 10-year career as an SDET to the fascinating world of Machine Learning. I'm currently upskilling and diving into coding projects to get hands-on experience in ML. But what ...
souvikdcoder's user avatar
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0 answers
19 views

How should I use ML to extract the entries from a dictionary?

A question about methodology I know that methodology questions are not welcome on the Stack Overflow site, but I don't know if they are acceptable here. If they are not, I apologize. Description of ...
lima's user avatar
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0 answers
23 views

why does my multi-modal model can not learn anything?

I have a multi-modal model. I want to train it using the Pytorch Framework. I have a balanced dataset. I have approximately 150 samples for each client. (I had preprocessed my text data.) when I train ...
arcane_data's user avatar
1 vote
1 answer
47 views

Packages for Density Estimation using K-Nearest Neighbor

I would like to have suggestions for packages that provide K-Nearest Neighbor density estimator, I've already searched the web (to not bother you guys with my question :) ), but most results were ...
Neyo Goldsmith's user avatar
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0 answers
44 views

Gradient function in LogisitcLoss class

I am going through a code for XGBoost from scratch and I am referring to this repository here The log-loss function is given by On differentiating the above function with respect to y_pred (referring ...
Mehul Jain's user avatar
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0 answers
12 views

Is AdaBoost an online classificer only?

I have been using CControl library for classify data. As I understand AdaBoost, it's an online non-linear classifier algorithm and not an algorithm, such as SVM, that gives you weights back were you ...
euraad's user avatar
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