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.
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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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Why are decision trees driven by the Gini impurity as opposed to the accuracy? [duplicate]
It seems that most implementations of decision trees use the Gini impurity as their partitioning criterion. Why isn't accuracy used instead, since it's a more widespread metric across different ...
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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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How to multiply the boolean/binary values in 1 row in a dataframe by the chr values in another row with the product landing in the original row
Suppose that I already know which subset out of a set of 30 candidate regressor columns are the true regressors included in the structural equation describing that dataset (because I do by ...
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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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Trying to make a visualization for training performance
I am using scikit learn's BayesianRidge model to fit a regression to tabular data of d features and N sample. I have already tested how well my model performs using a repeated kfold cross validation ...
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Ordering training text data by length
If I have text data where the length of documents greatly varies and I'd like to use it for training where I use batching, there is a great chance that long strings will be mixed with short strings ...
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How do well informed labels for ordinal encoding improve model performance?
From Kaggle's intermediate machine learning tutorial, it was stated that
for each column, we randomly assign each unique value to a different integer. This is a common approach that is simpler than ...
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Overall acurracy +/- E (with 90% C.I.)
I am assessing the accuracy of my classification model. I performed a 4-folds cross-validation and I obtained the following Overall Accuracy: OA = (0.910, 0.920, 0.880, 0.910). So, the average OA is 0....
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Cause of randomness in AUC score for GNN
I have implemented a GraphSAGE model using dgl for link prediction. On average the auc score of the model is ~0.7 but the score varies a lot for different runs. ...
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How to compute Minimum sample size for Cohen's weighted kappa with more than 10 categories?
I am working with a system that classifies some samples and then I am comparing results with the classification made from a specialist. So every sample has a TRUE value (made by the specialist) and a ...
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Do I need to use AUPRC for reporting classification results on an imbalanced dataset when the model was trained using upsampling and CV
I am working on a binary classification problem which dataset has about 5% of positive class samples. I split the dataset, 70% for training and 30% for testing. I used the test data only once for ...
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Genetic algorithms with severals keras model
I have a population of 50 individuals that are basically weights and biases.
The genetic operators are operational from them in order to compute and assign new weights and biases to their models for ...
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Changing a 0-1 column datatype from int64 to uint8 such as in pandas.get_dummies()
Is it advisable to change the datatype int64 of a 0-1's column to uint8 such as ...
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precision and recall at k for movielens dataset
I wanted to recreate a very simple collaborative filtering example with the 1M movielens dataset I have from Kaggle (https://www.kaggle.com/datasets/odedgolden/movielens-1m-dataset) and then ...
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How to optimize Pandas DataFrame reorganizing?
I have a DataFrame which looks like this:
date
person
value
2022-05-01
A
5
2022-05-01
B
4
2022-05-02
A
5
2022-05-02
B
9
I want to convert it to that form:
...
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Inference speed of ReLU networks
I'm fairly new in the topic, and I was wondering whether some of you can point to existing works in which the inference of deep neural networks with ReLU activation functions is tested on GPUs as a ...
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Detect change in performance of new rasa model
I have a rasa nlu model running to detect intents and entities. Whenever a new model is loaded by rasa after training, I want to know how good or bad it is from previous model.
What I am planning is , ...
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Doubt about comparison of Machine Learning algorithm
I read this article about the comparison of Machine Learning algorithm.
According to this article, there is some characteristics that define the ML models performance. I know that there are some ...
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Which classification_report metrics are appropriate to report/interpret for a binary label? Individual or macro average for both classes? scikit-learn
First, please forgive my ignorance; I am a newbie but dedicated to learning more.
Example: I have a using a random forest classifier to predict a binary outcome. The binary outcome equals 1 if people ...
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Imbalanced data set with Sample weighting - How to interpret the performance metrics?
Consider a binary classification scenario whereby the True class (5%) is severely outbalanced to the False class (95%). My data set contains numeric data. I am using SKLearn and trying some different ...
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The behavior of the cross validation error and training error in underfitting case is not clear
I currently study the "Machine Learning" course on Coursera.org by Andrew Ng, it comes to a topic that discusses the performance of learning algorithms under different conditions.
Here, we ...
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What could be good Perfomance Evaluation Metrics for a Data Scientist?
Background
I'm a Data Scientist and am being asked to come up with a set of metrics/KPIs to assess my annual performance, and things like bonuses (and in the worst case being fired) depend on that. ...
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How to implement kfold and cv into Hybrid feature selection and evaluate the classification model performance?
I have been working on a Hybrid feature selection combined with hyperopt package for hyperparameter tuning and I am thinking about evaluating the performance of several model classifiers. I looked ...
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Is sensitivity the same as recall in multiclass classification?
In Wikipedia, it is stated "In binary classification, recall is called sensitivity" under the Recall section. Are they both different in case of multi-class classification?
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How to run hdbscan clustering faster?
I'm using hdbscan to cluster embedding output from BERT, which took in a data file of >150k chat messages. The embedding process took a little over 4 minutes, but as of this writing the hdbscan ...
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What should be the ratio between training time and accuracy?
What should be the ratio between time and accuracy?
I mean when should you drop the accuracy a little bit but it will take less time for the Classifier/Regressor to run?
Edit: As part of my studies I ...
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Measure performance of classification model for training on different snapshots
I am trying to do binary classification on some chronological data. Let's assume we have weekly data from the first week of 2017 through the last week of 2020. Now we have found out that 26 weeks of ...
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How to compute performance of a detection-classification system?
I use a yolo (y) to detect only one object and a multiclassifier (mc) that classifies that object.
Now, the problem is: what I have to do with yolo's false positive and false negative, if I want to ...
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nested cross validation vs. train-test split
I am trying to understand the main benefits of conducting a nested cross-validation compared to a simpler train-test split. Let us say I would like to build a prediction model. I initially split my ...
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Performance measurement of an event extraction system
I have developed an event extraction system from text documents. It first clusters the data corpus and extracts answers for what, when and where questions. Final answers are determined by using a ...
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What is the Most Efficient Tool in Python for row-wise manipulation of data?
I'm doing a lot of work that requires operations to be performed across rows, using the data in that rows's columns on other columns in the row.
I recently had to do some processing on a 1.2 million ...
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Create new performance indicators (error metrics)
I am wondering if any of you happen to know of a procedure/approach/rationale to develop new performance indicators (error metrics) that can be used to evaluate the prediction capability (say, ...
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correlated variables & model performance: optimal trade-off
on the back of this topic (When to remove correlated variables) I feel a follow up is needed, with the focus here being on raw performance and risk of distribution shift.
assuming little to medium ...
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Creating a new feature from an existing one using decision trees
Is it possible to create a new feature out of two, or more than two existing features using a decision tree?
If so, how, and can it produce features with good information value that can better help ...
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2D Z-score/Mahalanobis distance that includes a penalty for uncertainty
I have some 2D points and I want to assess their performance against the target point.
When I was doing this in 1D, I took the Z-score Z = (x- mu)/sigma, but that ...
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KNN efficient implementation
The KNN algorithm is very handy and particularly suited to some of my problems, but I can't find any resources on how to implement it in production.
As a comparative example, when I use a neural ...
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How to increase accuracy and decrease loss of my model
https://jovian.ai/casella0798/badmodel
I created the model above to predict red wine quality. I have 6 classes, from 3 to 8. Dataset is unbalanced, with a lot of classes 5 and 6.
My model performs ...
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Choosing best model produced from different algorithms. Metric produced by cross-validation on the train set or metric produced on the test set?
I know that choosing between models produced by one algorithm with different hyperparameters the metric for choosing the best one should be the cross-validation on train set.
But what about choosing ...
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Once a predictive model is in production, how it can be evaluated?
I have a data science project, predicting customer's next purchase day. Customer's one year behavioral data was split to 9 and 3 months for train and test, using RFM analysis, I trained a model with ...
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CNN inference is slow on Jetson Nano
I'm running what I believe is a pretty lightweight CNN on an nVidia Jetson Nano with Jetpack 4.4.
nVidia claims the Nano can run a ResNet-50 at 36fps, so I expected my much smaller network to run at ...
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How do data types influence hardware (CPU / GPU / TPU) performance?
I am currently dealing with a relatively big data set, for which I have some memory usage concerns. I am dealing with most of the different data types : floats, integers, Booleans, characters strings ...
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What is the appropriate statistical significance test for multi-class classification?
I have a multi-class classification problem. I am primarily using macro-average F1 measure to evaluate the performance of models and want to verify if the results are statistically significant. I have ...
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Fast PR / ROC curves and corespondings AUPR / AUROC
I find myself in a position of calculating numerous PR / ROC curves and their associated area under the PR curves (AUPR) / area under the ROC curve (AUROC).
Its is quite easy to perform those ...
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How to balance time/effort with transformations, feature selection, and models efficacy in nlp? [closed]
Edit: Question has been edited for reopening (see comment section for justification)
Being to new text analytics, I haven't gotten the hang of navigating a typical workflow given the longer times ...
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Business-related metric for an optimization problem
We have an optimization problem on hand that is the following.
Let's say we have 10 different treatments that we might offer, all of them are equally good for us, but people have different propensity ...
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Is fitting two RandomForestClassifiers 500 trees each and average their predicted probabilities on the test set more performant than one with 1000?
If I fit two RandomForestClassifiers 500 trees each and average their predicted probabilities on the test set, would it have better results than fitting a RandomForestClassifier with 1000 trees and ...
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Using a random forest, would a RandomForest performance be less if I drop the first or the last tree?
Suppose I've trained a RandomForest model with 100 trees. I then have two cases:
I drop the first tree in the model.
I drop the last tree in the model.
Would the model performance be less in the ...