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27 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
23 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
20 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
20 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 ...
1
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1answer
17 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
12 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 ...
1
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1answer
26 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
41 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
31 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
45 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)
1
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1answer
35 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 ...
1
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1answer
12 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
21 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. ...
4
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1answer
144 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
216 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
9 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 ...
0
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1answer
12 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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0answers
80 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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0answers
11 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 ...
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0answers
12 views

Loss function for multi-class classifiction where output variable is a level i.e the various classes are dependent on each other

Let's say we are classifying Images of cat , fish and human. Classifying a cat as human is as wrong as classifying it as fish, so here the normal loss functions/ metrics like Confusion matrix is fine. ...
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1answer
18 views

How is the “loss” calculated which is supplied by the callback log in Keras?

I.e. categorical cross entropy? binary cross entropy? Something else? Or is it perhaps the loss function which you pass into the model.compile method?
2
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1answer
28 views

Metrics for Name Entity Recognition

Working on a NER project, I have been facing the problem of evaluating my model during training. I cannot be using the accuracy metrics or f1 score or any other metrics to evaluate my model on runtime ...
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0answers
32 views

For a multiclass classification problem, how do we find the cohen kappa score?

So I have a multiclass classification problem and I have found the Matthews Correlation Coefficient of that (https://scikit-learn.org/stable/modules/model_evaluation.html#matthews-correlation-...
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1answer
25 views

How is computed the train data set score and why?

In a lot of machine learning blogs or review, the training dataset accuracy (or other metric) is given alongside the test dataset score. Is this score calculated through the training, or is the ...
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2answers
20 views

I am getting different mean_absolute_error when i retrain my model everything same

I have set my numpy random seed to 0. I am training on colab and using keras. I didn't change anything. I just re-ran my cell and the val_absolute_error changed. Code: ...
0
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1answer
69 views

Best metric in imbalanced classification for multi-label classification

My test data are imbalanced, i tried to use the precision or the gmean as metrics for a multi-label learning model, but both metrics are not very informative. Is there any way to use for example the ...
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0answers
10 views

Manual setting of target variable based on features' minimum values: f1 score = 1

I am building a classifier for user engagement in my website. Basically, since there are no "proxy" for engagement, i.e. there is no pre-defined target variable, I came up with minimum thresholds ...
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0answers
30 views

What is divergence exactly in machine learning?

I know about KL divergence, JS Divergence and clearly know that it is different from the divergence in calculus. I have an intutive feeling of divergence as it roughly compares the closeness of two ...
1
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1answer
51 views

How to interpret metrics of a model after scaling the data

I have a GradientBoostingRegressor from scikit-learn which I trained. Afterwards, I obviously would like to know how good the model is. So, on a non-scaled dataset ...
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0answers
35 views

I got a overall mean average precision score of 0 for a recommendation engine

I just wanted to know if receiving an overall MAP score of 0 in a recommendation engine was possible, or a sign that my calculation or my logic for the engine was wrong.
0
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1answer
57 views

Metric (rather than RMSE, MSE, etc.) to choose the best model in terms of the ability to detect peaks better

I have created multiple regression models and wanted to choose the best one. One common metric would be RMSE, as you know. When I looked at the results, second model (RMSE = 0.15) was better able to ...
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0answers
13 views

How to measure the success of a seasonal product or what should be the northstar KPI

Not sure if this is the right forum to post this question. This is more of a product management question, I searched all the communities in StackExchange and thought this might be the closest to ...
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0answers
40 views

Is there a metric for counting AND classification simultaneously?

I'm working on a project that mixes object detection and crowd counting. The metric for object detection is mAP, which combines the regression of the bounding boxes with the precision of the ...
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3answers
556 views

How to compute f1 in tensorflow

I have code that computes the accuracy, but now I would like to compute the f1 score. ...
2
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3answers
110 views

How to select between models when AUC scores are similar?

I use two machine learning algorithms for binary classification and I get this result : Algo 1 : ...
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0answers
13 views

Metrics for stain normalization

Are there any metrics or methods for assessing stain normalization techniques?
1
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0answers
65 views

What does the ratio of precision/recall to their ideal values mean, and why are they equal?

When evaluating rankings, Normalized Discounted Cumulative Gain (NDCG) normalizes the score to a [0,1] range by dividing by the ideal score. What happens if we take the same idea to Precision (Pre) ...
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0answers
110 views

Using logLoss as metric function for highly unbalanced dataset

ihave an highly unbalanced dataset and the caret pacjage only allows me to select accuracy or kappa as performance metric. Is it correct to use a mlogloss function to compute model performance? Do you ...
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0answers
48 views

How to Monitor ML Classification Models in production?

I've often heard of measures like Population Stability Index and Characteristic Stability Index. I might be mistaken, but these seem to be more applicable towards looking at the changes in univariate ...
1
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0answers
99 views

how to interpret a high AUC value but a low F1 score after upsampling minority class?

I use to gradient boosting to classify my data between default and paid. The data is very imbalanced where default is in minority. The fisrt classification report from sklearn gradient boosting ...
1
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1answer
318 views

Can macro F1 score be greater than micro F1 score?

I am reading about evaluation metrics, and it seems that micro scores are more useful. But I was wondering about scenarios where macro F1 score is greater than micro F1 score, and if this is at all ...
2
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2answers
22 views

How should multiclass classifier performance be measured when one type of error is preferred over another?

Sorry if this question has been asked before--I am having trouble searching this topic since I'm not sure of my wording. Say you have a classification problem where there are more than two labels ...
1
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1answer
204 views

Metrics for presenting RNN/LSTM result

I am working on a two different architecture based on LSTM model to predict the users next action based on the previous actions. I am wondering, what is the best way to present the result? Is it okay ...
2
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3answers
53 views

A metric between trees

I have certain tree structures. I am not an expert in machine learning. As I would with take KNN, I would calculate distances via metric function and a new data point and the points from the training ...
0
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2answers
38 views

How to measure accuracy of a route prediction

I developed a new route prediction algorithm and I am trying to find a metric that informs on how well a prediction was. This metric is meant to be used offline, meaning that the goal is not to ...
2
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2answers
2k views

MAD vs RMSE vs MAE vs MSLE vs R²: When to use which?

In regression problems, you can use various different metrics to check how well your model is doing: Mean Absolute Deviation (MAD): In $[0, \infty)$, the smaller the better Root Mean Squared Error (...
4
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3answers
1k views

What is the relationship between the accuracy and the loss in deep learning?

I have created three different models using deep learning for multi-class classification and each model gave me a different accuracy and loss value. The results of the testing model as the following: ...
0
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1answer
58 views

Understanding the Gini/AUC metric as out-of-development performance metric

Assume we develop a model for a binary classification task that reaches a certain Gini/AUROC estimate on the validation ( or training ) sample, among others. This is an overall good metric, often used ...
2
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0answers
24 views

Dimension of the manifold on which my data sits

Suppose that I have data points, in the form of vectors with binary entries. We create a metric space, or Vietoris-Rips complex, using the Hamming distance between the data points. I would like to ...