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Public Email Classification Dataset but not Spam vs Ham

Context Working to deliver a POC on automated email classification (in customer service context) to tag emails as related to feedback, complain, lost and found etc. The tags are not entirely exclusive,...
Della's user avatar
  • 335
0 votes
0 answers
18 views

Finding accuracy of model that uses different labels than ground truth

I have an nlp model that has ground truth labels and predicted labels (that belong to different group of classes). For example, the ground truth labels are [art, computer science, history] and ...
Vidushi Maheshwari's user avatar
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0 answers
14 views

Image Generation Models

I am looking for a list of different image generation models and how I can test them? For example: DALL-E (accessible via ChatGPT4) Stable Diffusion (open source) CLIP? - but idk how to access/test it....
x89's user avatar
  • 191
0 votes
0 answers
16 views

Losing Information while resizing the image in Segmentation task using U-net

I'm using U-net architecture to build a segmentation task of image. During training I have image of size 256256 image. It works very well on the segmentation of same size 256256 or near to size 256*...
Akshit Dhillon's user avatar
1 vote
1 answer
21 views

Reducing emails token count preprocessing for Large Email Datasets - Feeding LLMs

I have a large email dataset in .txt format and want to feed LLMs (like Gemini and ChatGPT) to provide answers based on email content. The token count for my email data is very high (~1M for 1K emails)...
Rafael Borja's user avatar
0 votes
1 answer
15 views

Does nowcasting use cross sectional data?

So in recent months I have been reading about nowcasting. From what I understand what UMIDAS does is that it transforms the dataset into cross sectional data and then runs OLS. The more I read ...
J_Bake's user avatar
  • 1
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0 answers
6 views

DCGAN for mammograms

I'm currently working on a DCGAN with Wasserstein Distance Gradient Penalty (WGAN-GP) for mammograms. The target mammograms are in 4D, as I'm using SD VAE 1.4 to reduce the complexity. Each of the ...
Norhther's user avatar
-1 votes
0 answers
10 views

Delimited File Editor That's NOT Excel

I'm looking for Excel alternatives that DO NOT make assumptions about cell contents when opening a CSV or a similar delimited file. The text import wizard in Excel is not a viable solution: I don't ...
Tavaro Evanis's user avatar
0 votes
0 answers
6 views

MIT-BIH and ECG-ID for ECG Authentication System

Both the MIT-BIH and ECG-ID data files are stored in the Waveform Database (WFDB) file format. The record_name.dat file formats are binary files containing samples of digitized signals. So, can I ...
Mohamed Azab's user avatar
0 votes
1 answer
13 views

How to check if an event affects time series

We have time series data. Depended variable – interest rates, about 15 years, monthly data. Independent variable – event, rating announcement (rating may change or may not), happens 2-3 times per year,...
NoobinStatistics's user avatar
1 vote
1 answer
17 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
  • 11
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0 answers
18 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
13 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
0 votes
1 answer
15 views

can we use tanh activation function to detect outliers?

Can we use tanh activation function to detect outliers ? Does my image below true for dataset outliers (after training model with tanh activation function) ?
user3668129's user avatar
0 votes
0 answers
15 views

Variable Selection and model prediction

In a supervised problem, I used randomForest for variable selection to identify the most important features. Question: am I required to use a random forest model for subsequent predictions, or can I ...
Zakaria Faouzi's user avatar
0 votes
1 answer
21 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
-1 votes
0 answers
7 views

I want to send parallel inputs to LSTM layers each LSTM layer should recieve 60 timesteps of single feature. How should i shape my inputs

...
Shreedatta Nasik's user avatar
4 votes
1 answer
1k views

How do I prompt GPT-4 to look at a PDF in Jupyter Notebook?

I am a beginner. I purchased tokens to use GPT-4 and finally figured out how to import the GPT-4 model into my Jupyter Notebook. ...
Mas's user avatar
  • 55
0 votes
0 answers
16 views

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
1 vote
0 answers
20 views

Are formulas in the article incorrect?

I am learning about backpropagation in LSTM. I have been studying an article and watching two videos on the topic. The videos 1 and 2 repeat all the information from the article, but with additional ...
Тима 's user avatar
0 votes
0 answers
13 views

How to build a model where each data point has different levels of information?

Let’s say I want to predict the weight of a person given information about them; height & sex. Now, let’s say that that I have additional information about roughly 50% of the individuals included ...
the man's user avatar
  • 139
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0 answers
25 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
0 votes
0 answers
22 views

When can we claim that the training converged?

I've been working for a while in a binary classification problem with different types of neural networks. In this particular case, I'm using an 3-layer MLP with hyperbolic tangent activation in input ...
leapofFaith's user avatar
0 votes
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
0 votes
0 answers
9 views

How does hyperparameter tuning work for constructing/choosing a final model using Nested Cross validation?

I want to determine if XGBoost is better than random forest or logistic regression for building a binary classification model. The model will be a composite model, with a feature selection model to ...
reuben george's user avatar
0 votes
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
0 votes
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
0 votes
0 answers
6 views

What are approaches to identify the meaning of columns in a dataframe based on similarity to known column instances

In my domain we can perform upon to 12 tests on a substance, and record results for each of the tests at different pressures e.g. between 10 and 20 steps between 0 and 6000 psi. for each substance ...
user1199100's user avatar
0 votes
0 answers
6 views

How to get the feature names from a OneHotEncoder embedded in a ColumnTransformer?

How can I get the feature names from a OneHotEncoder embedded in a ColumnTransformer? The following piece of code: ...
Evan Aad's user avatar
  • 163
2 votes
0 answers
26 views

Correlation between predictions vs correlation between targets

In a multi-target model framework - where a separate model is estimated for each target - how can one take into account for correlations between targets during the training process ? For example say I ...
Kreol's user avatar
  • 121
0 votes
0 answers
10 views

Measures of efficacy for one classification models on the same data set with different numbers of classes?

I am currently doing a university project in supervised learning. The variable to be predicted varies across the integers [0,100] and my supervisor suggested to split this range into different classes ...
Oliver's user avatar
  • 1
0 votes
0 answers
5 views

Controlling the confounding effect on cross sectional data analysis

I have a cross-sectional study in which an effect (feature) is analyzed in multiple groups of disease severity status. All groups may have individuals with shared characteristics like age and sex, ...
Mr. Gulliver's user avatar
0 votes
0 answers
8 views

Computing empirical coverage in binary classification confidence estimation

I am trying to compute confidence interval empirical coverage. I have computed the confidence intervals for binary probability predictions. For example, the model estimates that there is probability ...
Tiago Melo's user avatar
0 votes
0 answers
14 views

(Tensorflow) How to speed up initialization of model.fit()?

So I'm working with a rather large dataset (perhaps not really by ML standards - but too big to fit into my computer's RAM at any rate). And so, I train the model by successively loading a subsample ...
Tom P's user avatar
  • 101
0 votes
0 answers
11 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
  • 1
0 votes
0 answers
6 views

Synthetic Control for intermittent treatment

I'm exploring the application of the synthetic control method (SCM) to analyze the impact of intermittent treatments or interventions on a target outcome. I'm interested in understanding how SCM can ...
Notorious's user avatar
0 votes
1 answer
15 views

Missing data in train set and test set

I have a dataset of N columns. Now I'm able to preprocess data and find a subset of features that I can use to train a model and make predictions. In the case where the train data has missing feature ...
0-0's user avatar
  • 1
0 votes
0 answers
10 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
0 votes
0 answers
10 views

graph signal in GNN

I am reading several materials about graph signal processing for a thesis on Graph Neural Network and i see that a graph signal is defined as a vector so each node signal is a scalar. In practice, a ...
endeavor's user avatar
  • 101
0 votes
0 answers
8 views

Missing Value in a dataset

i'm curently cleaning a dataset and theres a column called " Institution", it is needed for encoding and training the classification model later so it needs to be cleaned. In that column, ...
Harry lou's user avatar
0 votes
0 answers
15 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
0 votes
0 answers
10 views

Struggling with developing code for an online learning application utilizing ARFRegressor

As shown in the picture below, I have split the data but struggling to write the code for training the model and savinng the model in particular directory using pickle for future use. Any suggestions ...
RAJESH KOYI's user avatar
0 votes
0 answers
14 views

How to apply online learning with Lightgbm using River for regression [closed]

Is it possible to apply online learning for lightgbm regression using river and if poosible please share some source codes...
RAJESH KOYI's user avatar
1 vote
1 answer
32 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
0 votes
0 answers
17 views

Loss increase while accuracy also increase [duplicate]

I'm training a fairly large classification model,and I'm having the below results. ...
WillWu's user avatar
  • 1
0 votes
0 answers
15 views

Drum sound classification using RNN issues - help needed

I am new to the field of machine learning, even tho I have solid background in semi-related fields (am control system engineer by trade) and as a hobby project I wanted to work a bit with sound ...
APasagic's user avatar
0 votes
0 answers
10 views

Need to compare results using Ward's method

So I create clusters like this and StandardScale them ...
Poyo's user avatar
  • 1
0 votes
1 answer
20 views

why is my svm taking much time to run what changes should i make in my code?

...
Kshitija Thakur's user avatar
-2 votes
0 answers
10 views

Looking for someone experienced in Time Series Forecasting [closed]

I am looking for someone with experience in time series forecasting for a small project. 6-8 hours. Willing to pay.
Raj's user avatar
  • 1
1 vote
0 answers
8 views

Which statistical approach is best for diverse conversion rates in a controlled experiment?

Our software startup builds chat bots for ecommerce websites. The chatbot talks to customers that open the chat bot, and has the goal of closing the sale with the store’s main product. We have about ...
Rage's user avatar
  • 111

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