Questions tagged [auc]

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30 views

AUC on ROC Curve near 1.0 for Multi-Class CNN but Precision/Recall are not perfect?

I am building a ROC Curve and calculating AUC for multi-class classification on the CIFAR-10 dataset using a CNN. My overall Accuracy is ~ 90% and my precision and recall are as follows: ...
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1answer
17 views

AUC ROC Curve multi class Classification

Here is the part of the code for ROC AUC Curve calculation for multiple classes. ...
1
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1answer
42 views

Algorithm for Binary classification

I have a data set with huge number of features ( Approximately 3000) and a binary target variable . The reason I have too many features is because of one hot encoding many categorical variables in ...
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0answers
24 views

Trying to plot REC curve and calculate AUC in R but getting error

I am working on regression machine learning techniques and calculating AUC (plotting REC) by using below paper link: http://homepages.rpi.edu/~bennek/papers/rec.pdf My Code; REC <- function(y_val , ...
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0answers
11 views

How to compute a confidence interval for AUC?

I found that in results of several binary classification problems, people report an AUC value together with a CI. I wonder how those CIs are computed. Is there a close-formed formula to compute them ...
0
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2answers
62 views

Don't understand why I get an inverse ROC curve for SVM (Python)

I build an SVM classifier but get an inverse ROC curve. The AUC is only 0.08. I've used the same datasets to build a Logistic Regression classifier and a Decision Tree classifier, and the ROC curves ...
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0answers
18 views

confused AUC ROC score [duplicate]

I am working on binary classification problem, I try to evaluate the performance of some classification algorithms (LR,Decission Tree , Random forest ...). I am using a 10 fold cross-validation ...
5
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2answers
102 views

Confused AUC ROC score

I am working on binary classification problem, I try to evaluate the performance of some classification algorithms (LR,Decission Tree , Random forest ...). I am using a cross validation technique (to ...
0
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1answer
33 views

XG Boost result interpretation for unbalanced datasets (Accuracy & AUCROC)

My dataset is of shape – 5621*8 (binary classification) Label/target : Success (4324, 77 %) & Not success (1297, 23 %) (success and Not success were been ...
1
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2answers
56 views

Main options on how to deal with imbalanced data

As far as I can tell, broadly speaking, there are three ways of dealing with binary imbalanced datasets: Option 1: Create k-fold Cross-Validation samples randomly (or even better create k-fold ...
0
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0answers
29 views

Orange ROC analysis widget

ROC analysis widget has an option to change prior target class probability. I'd like to know, when and how it should be used. Playing with it changes the slope of iso-performance line. Each classifier ...
0
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2answers
18 views

Getting lower performance metrics when using GridSearchCV

I have defined an XGBoost model and would like to tune some of its hyperparameters. I am using GridSearchCV to find the best params. However, I also tried to fit the model on the entire training ...
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0answers
13 views

What is a right way to compare AUCROC between logreg and logregs on segments?

I built a logistic regression on the entire sample (first model), as well as regressions on separate pieces (disjoint) of same sample (set of models). What is the best way to compare the effectiveness ...
1
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2answers
43 views

How to compute AUC in gridsearchSV (multiclass problem)

I'm working on a multiclass classification problem, comparing results from SVM and Random Forest classificators. I would like to use gridsearchCV for hyperparameters tuning and find that AUC is the ...
1
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1answer
99 views

Confusion matrix and ROC AUC curves are not in sync

I created a classification model with three target classes and created a confusion matrix to measure the accuracy, here is the matrix code ...
-1
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2answers
131 views

Plotting ROC & AUC for SVM algorithm

Towards , the end of my program, I have the following code. model = svm.OneClassSVM(nu=nu, kernel='rbf', gamma=0.00001) model.fit(train_data) Output ...
0
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1answer
34 views

Confusion Matrix and AUC in univariate Anomaly Detection

In the code I upon a csv file which only has one column. The data in there in not that important just normal numbers. ...
4
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2answers
771 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 ...
2
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0answers
15 views

Connection between prob output LogisticReg/SVM and ROC

I have the following ROC generated using LPOCV and Logistic regression or SVM (l2 norm). Now, let's say I have a test set containing 10 patients and I get that the probabilities of those patients to ...
0
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1answer
104 views

Imbalanced dataset - Positive majority class

My dataset consists of 150 patients where 50 are controls/healthy (negative) and 100 are sick (positive). If I want my model to have high sensitivity at hight specificity, in other words to have low ...
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2answers
32 views

Will oversampling help with generalization (small imbalanced dataset)?

I have an imbalanced dataset (2:1 ratio) with about 60 patients and 80 features. I performed Recursive Feature Elimination (RFE) and stratified cross validation to reduce the features to 15 and I get ...
2
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2answers
37 views

How much can the AUC improve comparing the raw dataset and the feature engineered dataset?

Let's say I put the following two datasets in the best possible model (same model for both): A raw dataset, the variables as they came just from the query. A feature-engineered dataset, with hundreds ...
2
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2answers
99 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 ...
1
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1answer
11 views

Truncating float/doubles for reproducibility

I deploy machine learning models (typically GPU) to a variety of environments. I work sort of at the edge of ML R&D and devops, so I am really big into reproducibility, and one thing that drives ...
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0answers
59 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 "...
1
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1answer
364 views

XGBOOST missing_value feature degrades my performance?

I'm training an xgboost model for gout disease on a training set I sampled 1-to-7 case-control ratio (enriched in cases). I have 220 features and I reach a cross-...
1
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0answers
107 views

Regression for binary classification and AUC metric

In the kaggle forums I found an example model where someone was using XGBRegressor for a binary (0/1) classification problem (sorry, cannot find the link any more). This was for a competition where ...