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Keras Early Stopping: Monitor 'loss' or 'val_loss'?

I often use "early stopping" when I train neural nets, e.g. in Keras: from keras.callbacks import EarlyStopping # Define early stopping as callback early_stopping = EarlyStopping(monitor='loss', patience=5, mode='auto',…
Peter
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XGBoost and Random Forest: ntrees vs. number of boosting rounds vs. n_estimators

So I understand the main difference between Random Forests and GB Methods. Random Forests grow parallel trees and GB Methods grow one tree for each iteration. However, I am confused on the vocab used with scikit's RF regressor and xgboost's…
Jack Armstrong
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Encoding with OrdinalEncoder : how to give levels as user input?

I am trying to do ordinal encoding using: from sklearn.preprocessing import OrdinalEncoder I will try to explain my problem with a simple dataset. X = pd.DataFrame({'animals':['low','med','low','high','low','high']}) enc =…
Ayush Ranjan
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Joining tables from different locations in Bigquery

I have been trying to join two tables from different datasets that are in different locations but in the same project. However, I keep getting the error: dataset not found in US location. The datasets' locations are US and us-east1 Here is what I…
shivanshu dhawan
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Optimising for Brier objective function directly gives worse Brier score than optimising with custom objective - what does it tell me?

I am training an XGBoost model and as I care the most about resulting probabilities, not classification itself I have chosen Brier score as a metric for my model, so that probabilities would be well calibrated. I tuned my hyperparameters using…
Xaume
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Difference between Ridge and Linear Regression

From what I have understood, the Ridge Regression is just having the loss function for an optimization problem with the addition of the regularization term (L2 Norm in the case of Ridge). However I am not sure if the loss function can be described…
Panathinaikos
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What should be the labels for subword tokens in BERT for NER task?

For any NER task, we need a sequence of words and their corresponding labels. To extract features for these words from BERT, they need to be tokenized into subwords. For example, the word 'infrequent' (with label B-count) will be tokenized into…
PinkBanter
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Why does vanilla transformer has fixed-length input?

I know that in the math on which the transformer is based there is no restriction on the length of input. But I still can’t understand why we should fix it in the frameworks (PyTorch). Because of this problem Transformer-XL has been created. Can you…
Ann
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Which of the NIPS 2014 papers are most significant, and why?

As a newcomer to the field, I find many of the NIPS 2014 papers fascinating, but it is difficult for me to evaluate which ones represent real progress over current approaches. Which papers do you think are most significant and are likely to have a…
Michael R. Bernstein
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What are some standard ways of computing the distance between individual search queries?

I made a similar question asking about distance between "documents" (Wikipedia articles, news stories, etc.). I made this a separate question because search queries are considerably smaller than documents and are considerably noisier. I hence…
Matt
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Why gradient boosting uses sampling without replacement?

In Random Forest each tree is built selecting a sample with replacement (bootstrap). And I assumed that Gradient Boosting's trees were selected with the same sampling technique. (@BenReiniger corrected me). Here there are the sampling techniques…
Carlos Mougan
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How word2vec can handle unseen / new words to bypass this for new classifications?

In simple terms, if my classification is based on word2vec as features, what I am supposed to do, if a new word comes, which does not have a word2vec? I am trying to used word2vec or word vectors for classification based on entity. For example: I…
Sarath
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Can I use LSTM models to evaluate multiple, independent time series?

Let's say that I would like to predict the temperature tomorrow. I could use the approach whereby I train a model based on a time-series dataset collected from a single location (for example, see this excellent…
CharismaticChromoFauna
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Linearly increasing data with manual reset

I have a linearly increasing time series dataset of a sensor, with value ranges between 50 and 150. I've implemented a Simple Linear Regression algorithm to fit a regression line on such data, and I'm predicting the date when the series would reach…
ArunDhaJ
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How can we extract fields from images?

I am making an document parser which extracts data fields from the documents and store them in a structured way. Each field in my dataset is horizontal which is easy to extract. But the model fails on following type of example - Is there any way…
hR 312
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