Data Science Stack Exchange Community Digest

Top new questions this week:

Should I open abbreviations/acronyms in the text data, when training transformer model?

I am currently training a transformer model on text data. Is it a good practise to open abbreviations/acronyms in the text data? I did not dins any tips or recommendations about it on internet.

machine-learning deep-learning nlp transformer

asked by Ir8_mind Score of 1 answered by noe Score of 0

What to do if my dataset have only One instance for class in classification?

I am working on a benchmark dataset for text classification. The dataset has about 300 classes, and approximately 50 of these classes have a single instance. In a paper that used fine-tuning BERT, the …

deep-learning classification multiclass-classification bert

asked by mandana hosseini Score of 1 answered by iftiben10 Score of 1

Which desktop hardware is best for DL?

I will be building my home Deep Learning workstation. Right now, I’m digging for some time about the best HW to use for home conditions. The workstation will be used for my work as a developer, but I …

tensorflow gpu colab hardware memory

asked by Jaroslav Štreit Score of 1 answered by Nicolas Martin Score of 2

What does the output of an encoder in encoder-decoder model represent?

So in most blogs or books touching upon the topic of encoder-decoder architectures the authors usually say that the last hidden state(s) of the encoder is passed as input to the decoder and the …

deep-learning transformer encoder

asked by Marek M. Score of 1 answered by noe Score of 1

Help with gamers' model: Is there an special name for a classification model in which the positive case is certain but the negative case is uncertain?

Suppose that I possess a binary classification model, where the positive class is certain, and I am confident that the positive samples belong to that class, while the negative class is uncertain, as …

machine-learning classification

asked by Juan Esteban de la Calle Score of 1 answered by Erwan Score of 1

Which of 2 options is better practice for model optimization: 1) Nested CV wrongly averaging inner CV scores. 2) Two successive CVs on X_all. Altrntv?

Goal: Compare preprocessing methods, models, and hyperparameters without leaking into the final generalization estimate, applying cross-validation (cv), i.e. NOT applying any fixed train/test splits. …

machine-learning python cross-validation optimization hyperparameter-tuning

asked by le8rning Score of 1 answered by Erwan Score of 1

best algorithms for clustering customers, customer segmentation

I have a dataset mixture of categorical and numerical variable, I was wonder what are the best algorithms to cluster customers? how to find the underlying patterns that segments a customer??

clustering k-means pca spectral-clustering

asked by F.Hazratian Score of 1 answered by Sivadithiyan official Score of 0

Greatest hits from previous weeks:

Understanding predict_proba from MultiOutputClassifier

I’m following this example on the scikit-learn website to perform a multioutput classification with a Random Forest model. …

scikit-learn random-forest multilabel-classification

asked by Harpal Score of 48 answered by chrisckwong821 Score of 45

ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

Firstly I have a pandas series of recommended product (recmd_prdt_list). In this series there is a possibility of presence of deleted products. So as to remove deleted products from the recommended …

python pandas dataframe

asked by SRJ577 Score of 4 answered by Elliot Score of 5

How do you visualize neural network architectures?

When writing a paper / making a presentation about a topic which is about neural networks, one usually visualizes the networks architecture. What are good / simple ways to visualize common …

machine-learning neural-network deep-learning visualization

asked by Martin Thoma Score of 164 answered by Alex Lenail Score of 81

strings as features in decision tree/random forest

I am doing some problems on an application of decision tree/random forest. I am trying to fit a problem which has numbers as well as strings (such as country name) as features. Now the library, scikit-…

machine-learning python scikit-learn random-forest decision-trees

asked by user3001408 Score of 85 answered by rapaio Score of 75

K-Means clustering for mixed numeric and categorical data

My data set contains a number of numeric attributes and one categorical. Say, NumericAttr1, NumericAttr2, …, NumericAttrN, CategoricalAttr, where …

data-mining clustering octave k-means categorical-data

asked by IgorS Score of 198 answered by Tim Goodman Score of 180

Why do cost functions use the square error?

I’m just getting started with some machine learning, and until now I have been dealing with linear regression over one variable. I have learnt that there is a hypothesis, which is: $h_\theta(x)=\…

machine-learning linear-regression loss-function

asked by Golo Roden Score of 112 answered by Harsh Score of 71

RNN vs CNN at a high level

I’ve been thinking about the Recurrent Neural Networks (RNN) and their varieties and Convolutional Neural Networks (CNN) and their varieties. Would these two points be fair to say: Use CNNs to break …

machine-learning neural-network beginner

asked by Larry Freeman Score of 62 answered by J. O'Brien Antognini Score of 46

Can you answer these questions?

Im looking for good neurons silmilarity metric

Recently I managed to create simple neural network visualization, to help to understand how neural network works on the signal level. I also wanted to arrange neurons by similarity cause I was …

neural-network visualization unsupervised-learning

asked by dismedia Score of 1

Why shouldn't post modeling calibration be done on the training set

I’ve read in multiple places that calibration on model results shouldn’t be done on the training set (the set that the model is build on), but rather, on a set that the model have not seen. I failed …

probability-calibration

asked by Yue Y Score of 1

Object Detection: Setting threshold values as trainable parameters?

I am building my first object detection model (Mobilenet SSD, to detect animals in images) and happy with the current test results. When I tested it using images without bounding boxes, I noticed some …

machine-learning cnn data-science-model object-detection

asked by user27771 Score of 1