Questions tagged [classification]
An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.
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How to classify/recognize postage stamp varieties?
As a hobbiest stamp collector, I often run into the need for classifying stamps based on minute differences, such as these:
Now, I literally have thousands of them (in ziploc bags) and I am planning ...
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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 ...
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Calculate AUC-ROC and AUC-PRC for an LSTM Model
I have the following simple Bidirectional LSTM model for a binary classification task:
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Speaker Verification models on
I went through different articles of speaker verifications (ECAPA-TDNN, TITANET).
They trained on ...
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Can someone interpret my Binary Cross Entropy Loss Curve?
I am trying to understand my loss curve using : tf.keras.losses.BinaryCrossentropy()
Question 1: Based on my loss curve/accuracy, would it be wise to proceed to feed it into a ensemble learning model ...
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Training the neural network does not give the expected result
I'm trying to create a pytorch neural network capable of recognizing peaks in 2D graphs. Previously, I was able to get a result close to what I wanted, but it was not ideal and did not give a ...
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Deal with overlapping classes in classification modeling
I am currently working with a dataset comprising information about crop insurance for soybeans. My ultimate goal with this dataset is to create a classification model capable of predicting whether ...
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Classification techniques for continuous arrays as inputs and scalar categorical variable as output
a newbie here. If you had any ideas about the following, that would be great.
Suppose for a given data set:
T’s and Y’s are arrays with
T = [0 1 2 3 5 6 7]
Y= [4 7 9 3 6 1]
So at T=0, Y=4 and so on
Z =...
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Implementing Fuzzy Matching and NLP for Transaction Classification
I’m a trainee at a fintech startup, and I’m working on a project that involves classifying transactions using Natural Language Processing (NLP) and fuzzy matching techniques. The main goal is to ...
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Do LSTM, GRU and Transformer models with less layers and units perform better than larger models when classifying short text sequences?
I am working with a Kaggle dataset with short Twitter messages as text input. I made a copy here. When testing LSTMS, GRUs, bi-directional versions of the GRUs, and the Encoder layers of a Transformer ...
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Classifying Players as winners or losers
I have a dataset that I curated from a game that I play. There are currently 130 instances (i.e. players) and an innumerable number of features. Experience tells me <10 features would be sufficient....
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What are the drawbacks of utilizing sample weights in classification tasks?
In classification tasks, especially when dealing with unbalanced data, using sample weights can be beneficial. However, it's not always the default choice in ML libraries like AutoGluon ...
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Similarity Scores between SQL tables
I'm trying to figure out the best way to get started on a project.
I have two separate databases, one is a "Template" db and the other is "Content" db. For each table in the ...
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Rather than build a classification model, Is building an embedding regression model feasible?
Face recognition models like VGG Face are designed to have a classification head on top and then trained to classify face images, but after they are trained the classification head can be removed and ...
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Data augmentation technique not working correctly
Write a function that can shift an MNIST image in any direction (left, right, up, or down) by one pixel.6 Then, for each image in the training set, create four shifted copies (one per direction) and ...
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