Questions tagged [performance]
For Question about Performance of a data science, statistical or machine learning model. Performace is a direct way to measure the efficiency of model. The Performance measure deals with time, accuracy and scalability for improve the model.
175 questions
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Compare classification performance of dataset subsets
Let's say I have a dataset like this on which I want to perform classification: id feature class factor 1 ... 1 A 2 ... 1 B 3 ... 2 A 4 ... 2 B $\vdots$ How can I compare the performance of a model ...
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Why might transforming my features improve the performance on a simple decision tree?
The features & target in my dataset are very skewed. Could anyone explain why transforming the features & target (I'm using a Yeo-Johnson transformation) is significantly improving the ...
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In my case XGBoost is faster than LightGBM. How do I achieve better speed?
I hope that this place is the right one to ask the following question: I'm training a machine learning model. The train size is 85000x55. 49x ...
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What is appropriate Individual KPI for AI projects?
I work in the sales department of electronics component manufacturing company and we do data science projects using traditional algorithm like Random forests (success likelihood of design project), ...
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What is the most accurate way of computing the evaluation time of a neural network model?
I am training some neural networks in pytorch to use as an embedded surrogate model. Since I am testing various architectures, I want to compare the accuracy of each one, but I am also interested in ...
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How to evaluate the performance of a prediction model across multiple predictions of the same event?
I was thinking of a hypothetical situation where you have a prediction model that can be used to predict the winner of an upcoming football match between Team A and Team B. Say for the sake of the ...
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Why does precision decrease with inceasing threshold?
I've trained a Logistic Regression model using scikit-learns LogisticRegression class. I'm dealing with stock data so it's quite noisy and difficult to predict ...
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Seeking guidance on understanding graphics card parameters for deep learning training
I am currently in the process of purchasing a new Nvidia graphics card for training deep learning models, and I have a few questions regarding the parameters involved and their relationship to the ...
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This model is too slow. I'm looking for a good, fast-enough, out-of-the-box, pre-trained image classifier. Any tip?
I have been using this on a laptop without a GPU: https://github.com/pharmapsychotic/clip-interrogator Currently it takes about 10s to classify a single image on my own computer. I use ...
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How to reduce the false positives to improve the models performance?
I am currently building a binary classification model to predict order return rates. I used the GradientBoostingClassifier for training the model and also performed hyperparameter tuning using ...
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Imbalanced performance metrics in binary classification
I am developing a binary classification model using sklearn pipeline for preprocessing and a soft voting classifier (Adaboost and Extratrees with 50 estimators). The dataset (3 million rows) contains ...
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Applying the model on validation data achieves higher performance than on test set. Is this possible?
I trained a binary cross-validated classification model and got high performance (about 90) on the test data but when I apply the model to new unseen data to see how to performs, i get even higher ...
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Total Retention Rate Calculated from Categories
I am calculating retention for 3 categories and then total, and I am trying to double check my total, but my check formula isn't working. I am comparing the last 14 days (let's call it Period 1) to ...
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Quantifying the performance of Stepwise Regression ran on Monte Carlo generated datasets & comparing them to your method of interest
The source data files and scripts referenced here and from whom lines of code are included here can be found in my GitHub Repository for this collaborative research project exploring the properties of ...
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Why does Adam outperform SGD in logistic regression?
I am training a logistic regression model. In case it matters, the features are 1376-dimensional embeddings output from a neural network. I tried both SGD and Adam with a learning rate of $10^{-3}$ ...
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