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Explanation : Simpler models beat BERT base

I have been trying to train different models for a multi-class classification task of texts. My data set consists of rows of text and its label. The texts are short sentences. I tried the following ...
eya_bklt's user avatar
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LSTM Layer producing same outputs for different sequences

Currently I try to train on a multi-label language task with imbalanced class distribution. I have the following model, where I removed some of the feed forward layers to decrease factors in the chain ...
Thomas Christopher Davies's user avatar
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RuntimeError: mat1 and mat2 shapes cannot be multiplied (25x7 and 1x512)

I am dealing with multivariate time series forecasting using Transformers. below is my code step by step: After some preprocessing and windowing time series dataset … 1- Creating Mask function ...
Amir's user avatar
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1 answer
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Images used in training CNN model

I am training a CNN with RGB images, however, when i plot them, they display in a bluish color. How can I have these display in RGB. Also do you think this affects the model accuracy? The code i am ...
Se Rai's user avatar
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1 answer
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How to represent output layer if the action size changes dynamically?

I am new to ML and I need to train a chess agent using proximal policy optimization. Board is represented as string and the environment gives a list of valid moves for each step. ...
heyula's user avatar
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6 views

Understanding processors in huggingface tokenizer library

tl;dr What are the :0 and :1 in the following huggingface processors reference usage given on their page: ...
figs_and_nuts's user avatar
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Predict best chess move using RNNs

I am trying to do a project with AI: in which during any certain moment of a chess game i can predict, using a RNN trained on a kaggle dataset, the best possible move that i can make. I am having ...
user3253067's user avatar
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7 views

Model performance impact on social discrimination?

I am currently working on a project where the data concerns people and the dataset contain personnal data with sensitive attributes. (typically: age, sex, handicap, race). Now it seems there are ...
Lucas Morin's user avatar
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Custom loss function for multi label classification in catboost?

I have a data frame which I want to use for multi class classification problem. There are total 6 classes (say a, b, c, d, e, f). I want to improve the precision for three classes (say a, b, c) i.e. ...
SUNITA GUPTA's user avatar
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6 views

How can I leverage machine learning for log analysis?

I am new to data science and trying to find possibilities of using datascience in tasks. I have a set of logs which I want to convert to json. The logs are more or less of same format and I can write ...
SUNITA GUPTA's user avatar
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1 answer
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Implementing Dropout in Keras

I think I am not conceptually understanding "Dropout" in neural networks. I was under the assumption that a keep rate of 0.8 would set 20% of all the neurons to 0 for each training example. ...
Yash Mali's user avatar
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Should I log transform the data if the dataset is small?

Suppose I have a dataset with only about 25 rows. All the relevant columns are all integers. The ranges of them go from 1 million to 100 million, and the distributions are all skewed right. In this ...
DSGuest's user avatar
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23 views

Improving performance of anomaly detection using dataset?

I am leveraging an isolation forest model from the scikit-learn library for anomaly detection in a time series dataset where each point in the dataset is a data frame. However, I possess additional ...
SUNITA GUPTA's user avatar
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5 views

How are the words defined in the sentencepiece algorithm?

I am not able to understand how the sentencepiece algorithm solves the problem of handling the languages without a clear-cut concept of words My exact confusion is: It is mentioned that one of the ...
figs_and_nuts's user avatar
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Purpose of Azure Cognitive Search

Azure provides a service called Cognitive Search which is an intelligent AI-based search service based on advanced NLP. I tried this feature. And to make the search as efficient as possible, it ...
Apoorva's user avatar
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1 answer
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VGG16 Transfer Learning for image binary classification - suspected overfitting

I'm using VGG16 for transfer learning on a binary image classification task about human posture. The sample totaled about 2,000 images, with about 900 and 1,000 images in each category, respectively. ...
MaxHo's user avatar
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Working of 'Interpolation' to impute missing values & the importance of the order of data points for the process

Definition of interpolation - Interpolation predicts values at a point by studying its neighbouring points (within the same column), as opposed to data modeling where all the columns are taken into ...
Apoorva's user avatar
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R, Caret Predict(), and errors

So I've been playing around with/testing out a few ideas. I just wasn't sure though if there is a simple command you can use to have caret like send you back a list (or data.frame) of all the errors ...
Nevermnd's user avatar
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How can I detect patterns in a csv of numeric values ​with a success failure indicator?

Hello everyone I have a need and I would like help to identify the technological approach, I tentatively consider that I need unsupervised ml for the following: I have a data dataset about investment ...
Luis Madueño's user avatar
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1 answer
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Why the training accuracy stays high but validation accuracy does not change?

I have a binary classification problem. I get ROI mammogram images and then apply a decomposition algorithm and as output I get 5 images which summation of them results in the original image. Now, ...
Nmgh's user avatar
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1 vote
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How do I achieve MAE < 8 using ResNet50 on this dataset?

I've been up all night trying to achieve MAE < 8 for this age recognition dataset: https://people.ee.ethz.ch/~timofter/publications/Agustsson-FG-2017.pdf It is for an online class I am taking, the ...
YKY's user avatar
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1 answer
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CLIP Paper or CLAP Paper (I dont understand the loss function) - Can you help?

Can somebody help me understand this Contrastive Learning pretraining paper? This explanation comes from https://arxiv.org/pdf/2206.04769.pdf (page 2). I understand that they apply an audio encoder ...
Tom's user avatar
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0 answers
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why my training and validation loss curve looks like lognormal distribution?

I trained an XGBoost model and my training and validation curve looks like this? Is something weird I am doing? I have always seen it going from high to low or like a U-shape incase of overfitting.
learner's user avatar
  • 101
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0 answers
31 views

My machine learning model cannot classify data that it has never seen before

I am creating a spam identifier to detect wheter an email is malicous. The issue I have is my model using the RandomForest Classifier showed it was 99% accurate. csv: https://www.kaggle.com/datasets/...
John Adams's user avatar
2 votes
1 answer
108 views

Higher level sentence similarity (meaning instead of 'just' embeddings)

I am looking for the correct model / approach for the task of checking if two sentences have the same meaning I know I can use embeddings to check similarity, but that is not what I am after. I ...
Rob Audenaerde's user avatar
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0 answers
10 views

Inverse Laplacian of xarray

my question is related to calculating the inverse Laplacian of a xarray. Specifically, I want to solve the equation ∇^2 s = h+r+e for s in Python (where ∇^2 denotes the laplacian). Here, s is an ...
random human's user avatar
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1 answer
19 views

Use prediction after using get_dummies in pandas?

I found similar question on this topic but no answer was helpful. I had a data frame with a categorical column in it with 5 different values. I used get_dummies and used linear regression for ...
Ali.A's user avatar
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1 vote
1 answer
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how to get rid of unseen labels

I am trying to perform naive bayes, but my testing set has a large amount of unseen labels. I thought the easiest way fix this issue is to remove them from the dataset but I get the error, TypeError: ...
sophie_123's user avatar
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26 views

Best model for regression in this case?

I am doing some modeling to predict a variable of interest given a big set of features (500) for which I expect a considerable amount of interactions happening at least among some of them. I first ...
Mirko's user avatar
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1 vote
1 answer
36 views

How to filter a dataframe and get a sub data frame based on frequency?

I have a data-frame. Lets call it df. My data frame has a column with categorical values e.g. a column named Place. But the problem is that there are many different (string) values in that column and ...
Ali.A's user avatar
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1 answer
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Question about bias-variance trade off

This question is from a uni module about machine learning. I'm a bit stuck as I can't relate it to the bias-variance trade-off, to me the question implies all models have something to do with the ...
pixel.t87's user avatar
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Could we use another attention module on the outputs of the attention heads in the transformer architecture?

Before concatenating the heads in MHAtt, could we add another attention module with the heads as input to combine them? Thus, for each head we would get a value matrice enriched with the outputs of ...
d3nigma's user avatar
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0 answers
8 views

How to make duplicates unique in a DataFrame robustly?

I have the following table. I was able to parse it and display it as a DataFrame with pandas in python I need to change the Ref for every value that is duplicate such that it becomes unique. For ...
bem22's user avatar
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0 answers
22 views

Algorithms from R-statistics package Caret R Package- LVQ algorithm, is there similar in Python

In the R-statistics package : Caret R Package, they have the LVQ algorithm that is used for the purpose of "Feature Selection". I have used this to do some data science in R-stats over 6 ...
Palu's user avatar
  • 103
0 votes
1 answer
17 views

Is it possible to use the SODA tool as open source?

I was reading about the SODA tool and was wondering if it was free to use. As far as I understand, it has a SODA library and a SODA core, but they are all just clients for connecting to a cloud server ...
JustUser's user avatar
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0 answers
11 views

Is there an appropriate hypothesis test: Two samples, one only with one datapoint, non-normal?

I have two 'samples'. The first consists of approx. 400 physical measurements of a quantity (taken over one hour, and the real situation is not a steady state). They show a very skewed distribution ...
Mars's user avatar
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0 votes
1 answer
32 views

Is improving a Neural Network really just "trial and error"?

After asking on StackOverflow, I was redirected here, so I'm reposting this question. I am a PhD student in Computational Physics and I've started to study a bit of Neural Networks, and decided to try ...
Mauro Giliberti's user avatar
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0 answers
7 views

Demand Forecasting methods for hundreds of time series

I have TFL cycling dataset for the time period from JAN 2023 to JUNE 2023. I would like to forecast the demand or expected no. of trips for each station at every hour of the day. Post some data ...
a_jelly_fish's user avatar
0 votes
1 answer
18 views

Working with functions

What are some good sources for learning how to deal with functions in Python and R. I have used them a lot of times and they can be a bit challenging. I like to write out a plan of what I want done ...
Salem Abdulkerim's user avatar
0 votes
1 answer
23 views

Is there a derichlet-tree learning algorithm written in Python

I want to learn a decision-tree based on dirichlet distribution (namely a derichlet-tree). Which Python (or possibly other) libraries/packages enables such algorithm?
SSSOF's user avatar
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0 votes
1 answer
22 views

CNN training accuracy flatlines

I'm training a CNN from scratch to do tagging of images. And my training is going nowhere. I was hoping someone could help me identify an obvious error. I would like to end up with a network that ...
laslowh's user avatar
  • 101
0 votes
0 answers
8 views

How to control and optimize optuna

i'm here with a pretty open question. I'm using Optuna to fine tune a Catboost Regressor and i've found, trying a set of parameters by hand, that the "best params" it outputs are not the ...
Alessandro Togni's user avatar
0 votes
1 answer
33 views

Optimizing YOLO for Diverse Takeaway Item Detection: Single vs Type-Based Classes

I'm using YOLO to detect various 'takeaway' items, currently all marked as class 0, which vary very widely(like groceries) in shape and type. Considering the introduction of new items on which the ...
Mike Like's user avatar
0 votes
1 answer
21 views

In lightgbm,what is a uniform drop?

I read through document of lightgbm,it just tells this parameter, but didn't give much explanation for it. The explanation: ...
cloudscomputes's user avatar
0 votes
1 answer
23 views

Are my regression metrics value correct?

So im using a dataset for Wine Prediction where im using Linear Regression model to predict the prices. These are the steps i'm using: ...
Rushabh Kayadra's user avatar
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0 answers
22 views

Cross validation and standard error

I'm performing a CV and I need to report the score with its error, but it only returns the score's average from the folds. Is there a way to either show each folder's score or find the standard error ...
Rafael Vinícius da Silveira's user avatar
0 votes
1 answer
18 views

Does learning rate depend on input and output range?

I watched hours of videos on gradient descent and still feel pretty confused. Let's say I have a "model": y = x * w I use 2 as my target ...
Eugene's user avatar
  • 103
1 vote
1 answer
31 views

Minimizing error in cosine similarity

Presume I have a vector space, and I am attempting to compress it into a latent vector space, while minimizing error in cosine similarity between entries. Suppose that I know the actual cosine ...
Krystal Fox's user avatar
0 votes
1 answer
33 views

Python SK-Learn KNN Imputer ( "ValueError: could not convert string to float: )

I have data with missing values. All columns are integer, except for a column that has missing values. These missing values, were set with a "?" which was converted to NaN using the Numpy ...
Palu's user avatar
  • 103
0 votes
1 answer
15 views

Number of feature extraction layers in CNN

In a course I took about machine learning, we normally used about 2 feature extraction layers for image classification tasks, using MNIST or ...
evilmandarine's user avatar

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