Questions tagged [metric]

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What is evaluation metric for two sets? [closed]

I've two sets one is ground truth and other is output of my machine learning models. Assume my groundtruth set is A={1,2,3,4,5} and output of machine learning model is B={3,4,5,6,7,8}. One way I can ...
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10 views

What is the state of the art/research metric to compare ellipses but jaccard coefficient?

Im looking for the, if there is one, metric to compare ellipses with each other. Last time a had a similar dataset (malaria cells, now its pupiles) i used jaccard coefficient but that was more because ...
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24 views

Loss and Metrics for COCO Keypoints

I am using Keras to train different models on the COCO keypoints dataset. All of the models I am working with are used for image segmentation, so they output heatmaps corresponding to the labels. All ...
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1answer
19 views

Inception Score (IS) and Fréchet Inception Distance (FID), which one is better for GAN evaluation?

IS uses two criteria in measuring the performance of GAN: The quality of the generated images, and their diversity based on the entropy of the distribution of synthetic data. On the other hand, FID ...
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14 views

Is there a way to normalize a similarity matrix by row and column in a way such that only one entry per row or column is approximately 1

I am computing similarities between 2 vectors. My goal is to have approximately 1 matching sample with similarity ~1, for each sample, without having any samples that are similar to many other samples....
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2answers
27 views

Is it correct to define the F-measure as the harmonic mean of specificity and sensitivity in such a way?

It is common to define the F-measure as a function of precision and recall, as mentioned in [1]: $F_{\beta}=\frac{(1+\beta^2)PR}{\beta^2 P+R}$ However I came across some other cases, another ...
3
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1answer
42 views

AUC-ROC for Multi-Label Classification

Hey guys I'm currently reading about AUC-ROC and I have understood the binary case and I think that I understand the multi-classification case. Now I'm a bit confused on how to generalize it to the ...
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1answer
18 views

Recall score for each sample in multilabel classification

Does it make sense to calculate the recall for each sample in a multilabel classification problem? Suppose I have 3 data samples, each having its own true set of labels and predicted set of labels. ...
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1answer
25 views

How to re-train a model from false positives

I'm still a bit new to deep learning. What I'm still struggling, is what is the best practice in re-training a good model over time? I've trained a deep model for my binary classification problem (...
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1answer
24 views

what metrics to evaluate rank order results?

I have searched on stackexchange and found a couple of topics like this and this but they are not quite relevant to my problem (or at least I don't know how to make them relevant to my problem). ...
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0answers
18 views

Metrics - multi-class model comparisons

I am looking for a way to quantify the performance of multi-class model labelers, and thus compare them. I want to account for the fact that some classes are ‘closer’ than others (for example a car is ...
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47 views

Keras custom metrics - MAP and MRR

I am trying to build a LSTM model in keras where I have one question with 10 answers but only ONE among them is correct. So basically im tring to build a 10 class classification problem. As most of ...
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0answers
29 views

How to estimate the accuracy on a large dataset?

Given that I have a deep learning model(handover from former colleague). For some reason, the train/dev set was missing. In my situation, I want to classify my dataset into 100 categories. The ...
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13 views

goodness of fit metrics to compare neural network and GLM model for count data

I´m wodering if some of you have compared goodness of fit of a NN and a GLM model on count data and which metrics you used? In addition, the data I´m dealing with has a point mass at zero. Are there ...
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0answers
16 views

What is ERR@K metric and how to interpret it? [closed]

What is ERR@K (e.g. K=10)? what does this metric's value tell me?
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0answers
21 views

How to calculate precision and recall?

There is a class-imbalanced labeled dataset with 100'000 samples. 90'000 is "0" and 10'000 is "1". There is a model that predicts the labels. It was runned on the class-balanced (10'000 of "0" and 10'...
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2answers
67 views

What is AUC - ROC Curve?

AUC - ROC curve is a performance measurement for classification problem at various thresholds settings. ROC is a probability curve and AUC represents degree or measure of separability. Is Roc the ...
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2answers
127 views

What's a good F1-score in (not) extremely imbalanced dataset?

I have a dataset with around 4.7K focused on binary classification. Class proportion is 33:67. meaning Label 1 is 1558 (33%) and Label 0 is 3154 (67%) of my dataset. Is my dataset imbalanced? some ...
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1answer
66 views

Calculating Rank Ordering Error Metric for implicit recommendation

I'm reading Collaborative Filtering for Implicit Feedback Datasets. On page 6 they detail their evaluation strategy, which they define as mean Expected Percentile Ranking with the following formula: $...
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1answer
61 views

F1_score(average='micro') is equal to calculating accuracy for multiclasification

Is f1_score(average='micro') always the same as calculating the accuracy. Or it is just in this case? I have tried with different values and they gave the same answer but I don't have the analytical ...
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10 views

Rank impact of individual metrics on overall sales performance

I’m interested in learning about different methods to analyse sales data - at both store level and corporate. Essentially I have lots of performance metrics (~20) that break down the overall sales ...
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34 views

Tensorflow API: What does the metric `tf.keras.metrics.TopKCategoricalAccuracy` do?

According to the API doc, this metric "Computes how often targets are in the top K predictions." But how come the following codes prouce the result 1? 0.95>0.9>0.8>0.1>0.05, both 0.95 and 0.8 lead ...
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1answer
1k views

How to interpret classification report of scikit-learn?

As you can see, it is about a binary classification with linearSVC. The class 1 has a higher precision than class 0 (+7%), but class 0 has a higher recall than class 1 (+11%). How would you interpret ...
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0answers
20 views

How to create an roc plot and calculate AUC for an svm (that does not return probabilities)?

I have some SVM classifier outputting final classifications for every sample in the test set, something like 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1 and so on. The "...
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1answer
279 views

What is cohen kappa metric, implementation in Python?

Can somebody explain indetail explanation on Quadratic Kappa Metric/cohen kappa metric with implementation in Python
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1answer
589 views

What is Continuous Ranked Probability Score (CRPS)?

I came across some evolution metric at Kaggle: Continuous Ranked Probability Score (CRPS): Mathematically, $C = \frac{1}{199N} \sum_{m=1}^{N} \sum_{n=-99}^{99} (P(y \le n) -H(n - Y_m))^2,$ where P ...
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3answers
58 views

What is the difference between an RMSE and RMSLE (logarithmic error)? [closed]

RMSE vs RMSLE Root Mean Squared Error (RMSE) and Root Mean Squared Logarithmic Error (RMSLE) both are the techniques to find out the difference between the values predicted by the machine learning ...
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3answers
357 views

Cosine similarity vs The Levenshtein distance

Cosine similarity vs The Levenshtein distance I wanted to know what is the difference between them and in what situations they work best? As per my understanding: Cosine similarity is a measure of ...
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0answers
16 views

Categorical loss functions with similar properties to Kullback-Leibler loss function

When using the Kullback-Leibler divergence as loss function for predicting the probabilities of a categorical (multinomial) distribution, one of the properties is that the difference between $a$ and $...
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1answer
108 views

How to define quadratic weighted kappa as eval_metric in catboost classifier

I am using catboost for a multiclass classification problem. I want to use quadratic weighted kappa as the evaluation metric. Catboost already has WKappa as an eval_metric but it is linearly weighted ...
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0answers
331 views

How do I use Cohen's Kappa as a metric in a keras model for continuous output?

I am using keras to train a CNN on a dataset. The output should be a value from 0 to 4 and my training y values are integers in that range. I want to create a custom metric that rounds and clips my ...
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1answer
27 views

How to control the amount of positives in classification?

I have a basic, yet quite complex problem to solve right now. Let's say we have a training set of 20,000 samples in my training set, out of which 3 to 4% is flagged as "True", the rest is flagged as "...
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1answer
31 views

What is the meaning of the parameter “metrics” in the method model.compile in Keras?

I don't have very clear the meaning of the parameter metrics of the compile method of the class model in Keras: ...
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1answer
39 views

Metric/loss for bin classification

I have a model that has to classify inputs into one of 45 categories but those categories actually represent bins (e.g. bins 1, 2 and 3 are between 1 and 10, 11 and 20, 21 and 30 respectively). What I ...
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1answer
18 views

Book about distances for data science (can't remember the name)

I saw a book somewhere that listed a big amount of mathematical distance functions (the usual euclidean norms, the discrete distance, the hamming distance, etc) used for data science. The name of the ...
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6 views

What could be a Replacement Level to calculate some sort of a Wins Above Replacements for an Ecommerce business

I'm trying to create a metric for an ecommerce business. Just like Wins Above Replacements is a metric used in baseball to assess the achievements of a player as compared to a standard replacement ...
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1answer
35 views

Sanity check: low PPV but high AUC scores?

I have two algorithms running on a piece of data, both of which perform differently. One of them (call it A) consistently gets a positive predictive value of about 0.75-0.78. Looking at the AUC of ...
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1answer
63 views

It seems that the output of sklearn.metrics.pairwise.euclidean_distances is different to the formula on doc

The doc of sklearn.metrics.pairwise.euclidean_distances() gives this formula dist(x, y) = sqrt(dot(x, x) - 2 * dot(x, y) + dot(y, y)). Apply this formula to ...
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0answers
45 views

A metric to include both accuracy and time

Problem Statement : Given a signal, predict some property of the signal. Let's say for discussion here that this property is the frequency of the signal. Clearly the output will be a regression value ...
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0answers
36 views

Binary classifier on imbalanced dataset yields weird PR curve

I have a dataset with ~6M points, 9 features and two classes. The minority class represents just under 2% of the data. The data is first divided into 100 batches and a different classifier is trained ...
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1answer
122 views

Choice of f1 score for highly imbalanced dataset?

I am confused whether to use f1 score with 'micro' average or 'macro' average for better evaluation. Given my dataset is highly imbalanced(600:100000)
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1answer
68 views

Ball Tree and Pseudometrics

The docs for sklearn.neighbors.DistanceMetric state that in order to be used within the BallTree, the distance must be a true metric (i.e. be non-negative, 0 ...
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1answer
15 views

Appropriate model metric for a truncated response variable?

Here's a straightforward question I can't seem to find a good answer to. Let's say you're using some variables to predict age. I'm assuming a regression model is the right approach. In this case, what ...
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0answers
34 views

GridSearch on imbalanced multi-class dataset

I have an imbalanced multi-class dataset (GTSRB) and would like to use GridSearch to determine the hyperparameters for an SVM. As metric for the evaluation I chose F1 with average macro. ...
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1answer
223 views

Interpretability of RMSE and R squared scores on cross validation

I'm working on a regression problem with 30k rows in my dataset, decided to use XGBoost mainly to avoid processing data for a quick primitive model. And i noticed upon doing cross-validation that ...
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0answers
248 views

Finding linear transformation under which distance matrices are similar

I have n sets of vectors, where each set S_i contains k vectors in ...
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0answers
43 views

What is Bit Per Character?

What is Bits per Character (bpc) metric which has been used to measure the model accuracy with reference to text8 and ...
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1answer
13 views

what is the representation/meaning/implication in real life of $P(\text{+})$ in the wiki Drug testing Example about Bayes' theorem

In probability theory and statistics, Bayes' theorem (alternatively Bayes' law or Bayes' rule) describes the probability of an event, based on prior knowledge of conditions that might be related to ...
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219 views

What's the difference between these two custom sparse categorical accuracy functions?

I have a sequence classification model featuring CustomELMo Embeddings layer + BiLSTM + Fully Connected layer. I've found two custom metrics for sparse_categorical_accuracy, but can't wrap my head ...
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13 views

How to optimize MAPE in regression algorithms

I have a regression task where the label is varying from about 0.001 to 1000. One of the feature called group, for example, group A corresponding label from 0-0.1 and group G corresponding label from ...