Questions tagged [score]
The score tag has no usage guidance.
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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 ...
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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:
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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 ...
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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 ...
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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 ...
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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 :
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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
...
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117
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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 ...
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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 ...
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Score of ANOVA in selected features
I selected features using ANOVA (because I have Numerical data as input and Categorical data as target):
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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 ...
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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 ...
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339
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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 ...
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41
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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
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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
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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= ...
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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 ...
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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 ...
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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 ...
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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 ...
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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
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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 ...
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859
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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 ...
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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.
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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.
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228
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Is the F1 Score sensitive to the threshold?
Is the F1 score sensitive or indifferent to the threshold (for defining positive or negative)?
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53
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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 ...
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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 ...
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131
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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 ...
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398
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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-...
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