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Questions tagged [score]

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Use OpenNN for score matching

I‘m new to this topic and need some guidance. I would like to implement score matching (like sliced-score matching: https://arxiv.org/abs/1905.07088) in C++. OpenNN (https://www.opennn.net/) seems to ...
0xbadf00d's user avatar
  • 101
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1 answer
21 views

Best measure to inform how predicted value can differ from real one

I have trained a regression model and obtained a pandas series of the predicted values. I am working on a "calculator" that will be able to return a predicted value after entering an input ...
Paulina's user avatar
  • 15
0 votes
1 answer
26 views

What do I make of all classification scores being equal to 1?

I've built an XGBoost classifier on a dataset that has 51 columns and a 1000 rows with following code: ...
Somanna's user avatar
  • 103
1 vote
1 answer
755 views

How to compare $R^{2}$ of train and test data in a Deep Learning Neural Network Regression model?

I want to judge the goodness of my neural network regression model built using Keras Python Library. The problem is the following: from an input like (1000, 5000) so 1000 samples and each sample has ...
HelpNeederStudent's user avatar
0 votes
0 answers
43 views

Hello! I am create linear model in python, and have question. It's bad score or good score?

please, take me info, this bad or good? I am real don't understand.... i'm know, also when Mean Absolute Deviation (MAD): In [0,∞), the smaller the better Root Mean Squared Error (RMSE): In [0,∞), the ...
Iakov Andreev's user avatar
1 vote
1 answer
27 views

Best practice and starting point for designing a decomposable score metric

I need to generate a 'score' metric (out of 100) to summarise a number of other features, and to allow comparison between sets. Each feature in turn will be some numeric value (possibly another ...
TrewTzu's user avatar
  • 111
0 votes
1 answer
1k views

Why is gridsearchCV.best_estimator_.score giving me r2_score even if I mentioned MAE as my main scoring metric?

I have a lasso regression model with the following definition : ...
Echo's user avatar
  • 113
-1 votes
1 answer
29 views

Difference between the different measurement metric [closed]

Can someone explain what each of these mean? both in simple terms and in terms of TP, TN, FP, FN? Also are there any other common metrics that I am missing? F-measure or F-score Recall Precision ...
Sharhad's user avatar
1 vote
1 answer
164 views

Difference between model score on test part and Kaggle public score

I tested my CatBoostModel model on part of data and get 0.92 score, but Kaggle public score was 0.9. I found new hyperparameters via randomsearch, new model score was 0.925, but on Kaggle score fell ...
Dmitry  Sokolov's user avatar
1 vote
0 answers
26 views

Right way to compare model scores for Next Best Action

I have around 15 classification models for different products built in different ways (some are RF, some are Gradient Boosting, some were downsampled in one way, others in other way, some are built in ...
user8419142's user avatar
2 votes
1 answer
259 views

Score of ANOVA in selected features

I selected features using ANOVA (because I have Numerical data as input and Categorical data as target): ...
Mimi's user avatar
  • 45
1 vote
1 answer
317 views

Train score is very lower than Test score, is that normal?

I am working on very imbalanced dataset, I used SMOTEENN (SMOTE+ENN) to rebalance it, the following test is made using Random Forest Classifier : My train and Test ...
Mimi's user avatar
  • 45
1 vote
0 answers
24 views

interpolation - graphical quality evaluation

I try to compare different interpolation models quality and I'm looking for a graphical tool to do that. Application case: I'm not familiar with intepolation using neural networks. I decide to test it ...
lelorrain7's user avatar
2 votes
2 answers
382 views

how classification scores are interpreted?

I would like to know how to interpret classification scores (i am not sure about the word score or probability, please correct me). For example, for a binary classification positive values are ...
phillipe cauchett's user avatar
0 votes
1 answer
45 views

r2 for regression models it is a score or error? [closed]

some places I have seen it is called as score and some other place as error. Lets suppose r2=0.83 means that score = 83% and Error= 17% or vise versa
zack's user avatar
  • 79
1 vote
1 answer
73 views

cross validation on whole data set or training data?

I am always having cross validation score smaller then the training score and I am performing cross validation on just training data is that normal thing ? Kfold = 5
zack's user avatar
  • 79
1 vote
1 answer
608 views

Why there is very large difference between cross validation scores?

I have a very simple regression model and I am doing the cross validation. When cv=10 the highest score i got is 60.3 and lowest is -9.7 which is useless. Average will be 30. No of row data set= ...
zack's user avatar
  • 79
1 vote
3 answers
679 views

Precision and Recall Confusion matrix

I was wondering, is it a proper method to convey information via separate Recall and Precision Confusion matrix? I recently came across a paper which reported the following scores. I am puzzled and ...
Born2Code's user avatar
  • 337
0 votes
1 answer
45 views

How would you quantify an experience into a score without labeled data

How would you approach a scenario where you have to quantify an abstract notion like “customer experience” without having any labeled data? So basically what you have are bunch of variables that you ...
Corel's user avatar
  • 159
2 votes
1 answer
7k views

Sklearn classification report is not printing the micro avg score for multi class classification model

There are 6 class labels encoded as 0,1,2,3,4,5 While executing classification report score it outputs accuracy,macro avg,weighted avg .The micro average score is missing in the output . Im not ...
star's user avatar
  • 1,481
1 vote
1 answer
383 views

Cross-validation average score

I am using Repeated K-folds (RepeatedKFold(n_splits=10, n_repeats=10, random_state=999) from sklearn) to provide reliable scores for a linear regression on my ...
towi_parallelism's user avatar
1 vote
1 answer
3k views

shapes (127,1) and (13,) not aligned: 1 (dim 1) != 13 (dim 0) [closed]

i am try to find score of linear regression it gives me this type error my code is below ...
prakash tiwari's user avatar
1 vote
1 answer
2k views

ROC AUC score is better if test data is imbalanced

I have an imbalanced dataset and I'm using XGBoost to do binary classification. I used down sampling together with target and one hot encoding for train data. For ...
corianne1234's user avatar
2 votes
2 answers
937 views

Compare scores of models

We got several models with predictions. How can we compare scores of different models with each other? We assume that we got xgboost models and scores distribution can be different for each model, so ...
Vladimir Ershov's user avatar
3 votes
1 answer
6k views

Can anyone explain me the fisher score working

I have been working on feature selection and I wanted to know what does fisher score tell us about the data which helps us in feature selection.
raghav gaur's user avatar
1 vote
0 answers
24 views

Multi-label learning, how to interpret the scores of instances

I am working on a multi-label learning classification problem. When I tune the hyperparameters of the model, the sign of each label (each line on the MLL) remains the same while the scores change. ...
Born New's user avatar
6 votes
2 answers
236 views

Is the F1 Score sensitive to the threshold?

Is the F1 score sensitive or indifferent to the threshold (for defining positive or negative)?
Juan Esteban de la Calle's user avatar
1 vote
0 answers
54 views

Calculate rating based on different parameters

I want to predict the rating of an area based on different parameter like crime rate, number of malls, number of hospitals etc. There is no historical data available, so I don't have any training data ...
Tarun Nagpal's user avatar
2 votes
0 answers
417 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 ...
irkinosor's user avatar
  • 233
3 votes
2 answers
150 views

How to measure variable contribution to an observation in a non-linear model?

Based on my model, if I decline someone due to their score, it should be able to provide some reasoning as to which variables mainly contributed to the decision to decline. Typically in Logistic ...
rayven1lk's user avatar
  • 371
0 votes
1 answer
426 views

Policy Gradient Methods - ScoreFunction & Log(policy)

In Policy Gradient Methods, Lecture 7 (34:15), David describes a Score Function as being the Gradient of the Log of the policy Question: If we have a Neural ...
Kari's user avatar
  • 2,736
0 votes
2 answers
290 views

recommender system: how to compare different scores when calculated individually?

I am building a small recommender system which aims at recommending ~10 products to customers. Instead of using a multi-label classification model, I have opted to build a separate scoring model for ...
Tanguy's user avatar
  • 270
-1 votes
1 answer
2k views

How to get relevancy score of a term with respect to text/document

I am working on the literature documents. I am able to identify important entities using NER and Ontologies. Now I will like to assign the relevance score to the identified entities with respect to ...
NKS's user avatar
  • 99
2 votes
1 answer
124 views

SKLearn DT regressor - good enough score?

What constitutes as a "good enough" score for a Decision Tree Regressor? The .score() function gives us a general score about our model. This can be 1 if the model ...
lte__'s user avatar
  • 1,320
1 vote
0 answers
91 views

Score for concordance of two classifications with different number of classes

I am searching for a score to compare two different classifications of the same observations. I was thinking about Adjusted Rand Index or Adjusted Mutual Information, but the problem is that the ...
gc5's user avatar
  • 879
1 vote
1 answer
1k views

Average F1 Scores scikit-learn

I know there is f1_score metric to get all types of F1 scores (micro, macro, and weighted); however, I would like to be able to print micro averaged F1 score using classification_report of scikit-...
Hima Varsha's user avatar
  • 2,346