Questions tagged [average-precision]
For questions related to the Average Precision metric.
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Average precision in in calssification vs in object detection
I think I understand what average precision is: the area under the precision-recall curve.The curve is constructed by calculating the precision and recall metrics at each threshold. There are a few ...
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Is there a way to effect the shape of precision-recall curve?
As long as I know, for both ROC and PR curves, the classifier performance is usually measured by the AUC. This might indicate that classifiers with equivalent performance might have different ROC/PR ...
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Regarding area ABOVE the curve - complement of AUROC
When handling probabilities close to 1, it is often more helpful to use the complement (i.e. 1-P).
For instance, we say "there is a 1 in 1,000,000 chance of an event occurring", instead of &...
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Comparing AUC-PR between groups with different baselines
So I know that the area under the precision-recall curve is often a more useful metric than AUROC when dealing with highly imbalanced datasets. However, while AUROC can easily be used to compare ...
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Better in AUC and AUC PR, but lower in the optimal threshold
Suppose we have two models; model A and model B.
Model A outperforms both AUC ROC and AUC PR to model B.
However, when we compare the two models with their optimal threshold values, model B ...
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Does a model with 0.5 AUROC imply an average precision equal to the proportion of positive examples?
A random model has an area under the ROC curve equal to 0.5.
We also know that a random model has an area under the Precision-Recall curve equal to the proportion (p) of positive examples.
Then, here'...
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Can the Dice coefficient be used for Mean Average Precision for Instance Segmentation?
I'm a beginner to computer vision currently working out a 2D multi-class instance segmentation problem on an imbalanced dataset of images with masks (98% background, 6 object classes for the remaining ...
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Average Margin of Error
Sampling 100 random respondents for a binary true/false response from a total population of 220,000,000 yields a margin of error of 9.8%.
If a new random sample of 100 respondents from the same ...
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roc-auc≈0.5, accuracy≈precision≈average_precision≈65%, recall≈1 [closed]
After reading this and this
, I tried it on mine by fitting the 2-input model i.e. text and numerical. The result remains similar even several attempts on tuning the hyperparameters e.g. embedding ...
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Questions about mAP results from YOLOv2 paper
In the YOLOv2 paper, is the mAP metric displayed in Table 3 calculated in the same way as the metric in the column '0.5' from Table 5?
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Can you estimate average precision from log loss?
I am doing my final thesis in the field of Deepfakes and their detection. The final outcome is to have a binary classifier which could predict which video was updated and which was not. In other words,...
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What is the average precision in the case of no positives for a given category in the context of object detection
In attempting to calculate the average precision of an object detection model, I am wondering about an edge case. Suppose at evaluation time that for a given category, that no detections of that ...
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Sklearn Average_Precision_Score vs. AUC
Can someone explain in an intuitive way the difference between Average_Precision_Score and AUC?
I read the documentation and understand that they are calculated slightly differently. But what is the ...
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XGBoost Mean Average Precision eval_metric for Classification
I am testing XGBoostClassifier for a binary classification problem. I have tried a few base models, done some simple parameter tuning, and performed feature selection using sklearn's ...
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how to find mean average precision of object detection algorithms
To start with, I would like to mention another question which was asked in a better way. But my problem differs.
pseudo code for the algorithms
I have four different object detection algorithms which ...
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How can mAP be less than all of mAP_S, mAP_M, and mAP_L?
I was looking at this graph from Learning Data Augmentation Strategies for Object Detection and I noticed that the value for mAP is lower than all of mAP_S, mAP_M, and mAP_L for the third set of ...
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Is it better to compute Average Precision using the trapezoidal rule or the rectangle method?
Background
Average precision is a popular and important performance metric widely used for, e.g., retrieval and detection tasks. It measures the area under the precision-recall curve, which plots the ...
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Acceptable level of mAP in computer vision applied to health applications
EDIT:
This question is meant for those who previously understand what mAP means but for contextualizing this question properly, it is the mean average precision as defined by Microsoft COCO i.e. the ...
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Calculating three average precisions and a single value for ROC from raw predicted class outputs
I'm not a statistician or mathematician so I apologize if I use any terms incorrectly. Please do point out any errors in my use of terminology.
The four values I need are the equivalent of Weka's ROC ...
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performance measure suited for imbalanced classes and robust towards changing class ratios
I am looking for the best performance measure.
My use case: I want to find out which dataset can be modelled best with binary classification. The datasets have an active minority class I am ...
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Confusion about computation of average precision
I am trying to learn what AP (average precision) means and I came across this page: https://towardsdatascience.com/breaking-down-mean-average-precision-map-ae462f623a52
Here is the given formula:
...
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How to calculate ± deviation for precision and recall?
I found a precision and recall report table like as below
Precision Recall
.470±.009 .934±.013
.239±.010 .610±.013
I need the guidelines for ±.009 and ±.013 ...
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Calculating sklearn's average precision by hand
I'm trying to understand how sklearn's average_precision metric works. The reason I want to compute this by hand is to understand the details better, and to figure ...
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Is it normal to have higher cross validation score IN EACH ITERATION than testing score
I'm using 10 fold stratified cross validation, training:testing is 0.75:0.25. Balanced data.
I'm using cross validation when doing feature selection with the 0.75 training data. The score I'm using is ...
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Computing average precision metric and cost function for object detection task using scikitLearn and Tensorflow
I have a Data set that contains 5 thousand pictures of my object of interest and 5 thousand pictures with out it. I trained a Convolutional Neural Network using Tensor Flow to detect the position of ...
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Intuitive or quantitative explanation of why we care about mean average precision (mAP) for CNN classifiers?
Consider CNN classifiers applied to some image classification tasks: to fix ideas, let's consider the ImageNet Challenge, where each image belongs to 1 of 1000 nonoverlapping classes, even though the ...
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mAP calculation in object detection
I'm quite confused as to how I can calculate the AP (average precision) or mAP (mean average precision) to evaluate an object detection model.
I specifically want to know if the True Positives (TP) ...
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Average precision when no relevant documents are found
I am building an algorithm that attempts to return relevant documents. If the query retrieves 10 documents but none are relevant how is the average precision calculated? Applying the AveP formula, it ...
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What does it mean if the ROC AUC is high and the Average Precision is low?
I have a model that produces a high ROC AUC (0.90), but at the same time a low average precision (0.30). From what I've found, I think it might have to do something with imbalanced data (which the ...
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Evaluating rare event risk metrics
Suppose there is a rare event that happens on 3-7 days a year, and we are interested to predict days when it happens. We have two metrics, A and B, that both take values on onterval (0, 1) for any ...
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How to count precision and recall for multiclass classification which returns top-5 classes per test example
This is how testing looks like:
There is 100 target classes
The test set consists of 10K elements - each one of them is tagged by one target class
The distribution of classes over test set is ...
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Using micro average vs. macro average vs. normal versions of precision and recall for a binary classifier
I have a logistic regression recommender model built on my data where I tried to predict one of two outcomes for each row. Let's call them success and ...
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How can the mAP metric be meaningful for non-exhaustively labeled datasets (such as YouTube BoundingBox)?
I am interested in reproducing the object detection results found in the whitepaper describing the YouTube BoundingBox dataset (https://arxiv.org/pdf/1702.00824.pdf). What I don't understand is how ...
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How to compute a precision-recall curve for an instance segmentation algorithm?
Having currently read some papers about proposed solutions to the problem of instance segmentation in images, (i.e. an algorithm that takes as input raw images, and outputs instance-wise segmentation ...
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Average Precision in Object Detection
I'm quite confused as to how I can calculate the AP or mAP values as there seem to be quite a few different methods. I specifically want to get the AP/mAP values for object detection.
All I know for ...
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Is an Average Precision of 60% acceptable output in a fraud detection machine learning algorithm? What does it signifies?
First question here, I am new to machine learning and wanted to understand the following:
I used decision trees, boosting to classify fraud users and I am getting average precision around 60% on my ...
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How to calculate mean average precision given precision and recall for each class?
I use Pascal VOCdevkit to calculate object detection average precision for each class, but how can I get mean average precision for the whole dataset? Should I average each average precision or should ...
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Absolute Average deviation in percentage calculation
Sorry if my terminology is incorrect.
I am trying to calculate the average error of prediction to be represented in percentage. For example, I should be able to say, the predicted values are on ...
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Calculating the standard deviation of the mean of average rates of speed
Is it possible to determine the mean value of a point by averaging the average rate of ranges that contain that point, and if so, how can the uncertainty of that value be accurately determined?
I ...
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determine the mean cost per unit
I have N orders. Each order consist of x units and I know the total cost of each order. If I would like to determine the mean cost per unit do I use approach 1 or 2 listed as follows:
(1) Determine ...
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Area under Precision-Recall Curve (AUC of PR-curve) and Average Precision (AP)
Is Average Precision (AP) the Area under Precision-Recall Curve (AUC of PR-curve) ?
EDIT:
here is some comment about difference in PR AUC and AP.
The AUC is obtained by trapezoidal interpolation ...
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Average precision when not all the relevant documents are found
I can't find on the Internet a proper source that explains this.
I have built a search engine that for a particular query retrieves 5 relevant document out of the 10 relevant documents.
When I ...
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Obtain Precision and Recall from Click through data
I am trying to build a graph of precision and recall using click data. I have two data sources.
First data source has all the user clicked item_ids based on a given query_id.
Second data source has ...
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Statistical significance test for multiple binary classification problems
Let $C_1$, $C_2$ be two binary classifiers, which are used to classify some data (images, videos, etc) to $30$ different classes, using an one-against-all approach. Then, we have two $30$-dimensional ...
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Mean Average Precision vs Mean Reciprocal Rank
I am trying to understand when it is appropriate to use the MAP and when MRR should be used. I found this presentation that states that MRR is best utilised when the number of relevant results is less ...
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Baseline for Precision-Related Metrics [duplicate]
When working with ROC-AUC as a metric for binary classification, one often considers a value of 0.5 as a baseline from a random classifier (i.e. a data-blind classifier that randomly classifies test ...
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How to compare two ranking algorithms?
I want to compare two ranking algorithms. In these algorithms, client specifies some conditions in his/her search. According to the client`s requirements, these algorithm should assign a score for ...
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Average of percentages / prove causal relationship between sale dates & margin sales
I just wanted to make sure I'm right here. I have a situation where I need to prove that on days where we sell more than 10 items, our margin (sale price vs. suggested price) goes up. I'm not really ...
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"Mean average precision" (MAP) evaluation statistic - understanding good/bad/chance values
I'm evaluating a multilabel classifier. I'm familiar with the Area Under the Curve statistic, which has some nice properties (e.g. chance level is always 50%). But for some applications, it's more ...
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Mean Average Precision (MAP) in two dimensions
I want to compute Mean Average Precision (MAP) from Average Precision (AP) over all users and over every 5 minute intervals of a day. How do I compute MAP from AP for both these dimensions [user, time ...
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