Questions tagged [score]

The tag has no usage guidance.

Filter by
Sorted by
Tagged with
0
votes
0answers
16 views

Effect of missing annotations in the ground truths on object detectors

I wanted to know whether not annotating some categories in our images, and feeding them into our neural network, would have any adverse effect on our model in detecting the desired objects. To better ...
1
vote
0answers
27 views

Standardizing binary decision with other scales (Like 1-5)

In the company I work for there are 2 different evaluation metrics for a song: Yes / No (Equivalent to like/dislike) 1-5 Scale Customers can use both to rank songs they like. I would like to create ...
2
votes
0answers
19 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 ...
2
votes
2answers
29 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 ...
0
votes
1answer
29 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
1
vote
1answer
25 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
1
vote
1answer
40 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= ...
1
vote
3answers
78 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 ...
0
votes
1answer
28 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 ...
2
votes
1answer
2k 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 ...
1
vote
1answer
108 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 ...
0
votes
1answer
819 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 ...
1
vote
1answer
367 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 ...
2
votes
2answers
180 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 ...
2
votes
1answer
1k 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.
1
vote
0answers
22 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. ...
6
votes
2answers
127 views

Is the F1 Score sensitive to the threshold?

Is the F1 score sensitive or indifferent to the threshold (for defining positive or negative)?
1
vote
0answers
38 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 ...
1
vote
0answers
249 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 ...
3
votes
2answers
56 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 ...
0
votes
1answer
218 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 ...
0
votes
2answers
237 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 ...
-1
votes
1answer
1k 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 ...
2
votes
1answer
65 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 ...
1
vote
0answers
60 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 ...
1
vote
0answers
848 views

Average F1 Scores - scikit learn

I know there is f1_score metric to get all types of F1 scores(micro, macro and weighted). But I want to be able to print micro averaged F1 score using classification_report of sklearn. By default, it ...