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Questions tagged [confusion-matrix]

A confusion matrix is a special contingency table used to evaluate the predictive accuracy of a classifier. Predicted classes are listed in rows and actual classes in columns, with counts of respective cases in each cell.

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278 views

Comparing multi-class results with binary classification results

We used machine learning to discriminate the following five disease classes: Normal (N) Myocardial Infarction (MI) Coronary Artery Disease (CAD) Congestive Heart Failure (CHF). In the past, these ...
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372 views

what's the best way to plot a confusion matrix in a multilabel setting?

In a multilabel setting a training example could be a, b, (a, b), d, c, (d, c), etc. This makes it a bit hard to come up with a helpful confusion matrix because the ...
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1answer
36 views

how can I replicate working of Multi Label Binarizer from sklearn package in R?

I want to achieve same working of MultiLabelBinarizer from sklearn.preprocessing package in R. I have list of labels for each example (for Predicated and Actual) like below. ...
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2answers
154 views

How do I calculate the range of a F1-score from a confusion matrix of 3 class,A,B,C

Is there any support function to calculate the average F1-score range?
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0answers
78 views

Is this analysis good or not?

I am doing a project in plant pest detection using CNN. There are four classes each having about 1000 images.I have use alexnet architecture for training. I think confusion matrix is not correct. What ...
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1answer
112 views

How to decide optimal threshold for my classification model from FPR, TPR and threshold

I am building my model in Python to classify customer in buyer/ non-buyer category. I used mutiple agorithms for this problem and then after evaluation selecting the best out of all. sklearn package ...
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13 views

Compute an ROC for a hybrid model where only one of the model components computes class probabilities

I've created a hybrid model by taking an existing decision engine (TRUE/FALSE output) and supplementing it with a random forest ...
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0answers
2k views

Can tuning individual precision and recall classification thresholds improve deep learning models?

I learned that Keras doesn't have a built-in way to set a threshold for precision and accuracy when building a classifier. Courtesy of a solution here, I wanted to see what would happen when I fit a ...
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0answers
46 views

Trying to come up with a feature to improve emotion classifier based on facial movement using facial landmarks

I managed to create an emotion recognition system that uses dense optical flow on each entire frame. While the accuracy range is within 80-90% with cross-validation, I am aiming to improve the ...
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7 views

Precision-Recall for CNN place recognition problem

Given 3450 query and 3450 reference images in a place recognition problem, I plot the ...
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1answer
49 views

What does the KFold error mean and how to get confusion matrix from Kfold random forest implementation?

from sklearn.model_selection import KFold num_folds = 10 seed = 77 kf = KFold(n_splits=num_folds,random_state=77,shuffle=False) rfc=RandomForestClassifier(...
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61 views

Do I use class weights to penalize false negatives or threshold optimization to improve recall?

I built a Random Forest model for a binary classification problem.Both the classes in the target variable are balanced. My main class of interest is 'class 1'. False negatives are more costly to me, ...
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48 views

How to plot a wordCloud for essay text from a confusion matrix false positive rate count?

I have an essay of text(BOW) and I have modelled it using let's say any model and plotted the confusion matrix and that I have got FPR, I need to plot a word cloud which shows the words due to which ...
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41 views

For a multiclass classification problem, how do we find the cohen kappa score?

So I have a multiclass classification problem and I have found the Matthews Correlation Coefficient of that (https://scikit-learn.org/stable/modules/model_evaluation.html#matthews-correlation-...
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73 views

Why is the random forest confusion matrix for my test dataset 100% accuracy, when training data matrix isn't?

I am using the software Orange to undertake a random forest classification of geo-chemical data. I am trying to classify points as 0 or 1 based on whether it is a mineral occurrence or not. My ...