Questions tagged [accuracy]

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3 views

Is there any way to calculate the true,false positives and negatives for a regression problem

I am trying to predict the glucose values of the patients for example values like 45,256,115 etc. based on some features. Currently I am calculating the accuracy in means of RMSE,MSE,R². Is there any ...
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1answer
19 views

Same validation accuracy, different train accuracy for two neural networks models

I'm performing emotion classification over FER2013 dataset. I'm trying to measure different models performance, and when I checked ImageDataGenerator with a model I had already used I came up with the ...
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2answers
43 views

is it ok to get 100% accuracy in random forest classifier algorithm?

while i was building the model to predict the performance of machine using the features like OEF,working time,performance/head etc... I splitted the training data using ...
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1answer
21 views

Using standard deviation as a metric for model selection

I'm really getting stuck with overfitting and I'm trying all I can to reduce it. I want't to write a metric to help score models in a cv loop. I'm using 10x5 folds and still getting out of sample ...
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10 views

Can a binary classification model have lower accuracy, but higher F1-score [duplicate]

I am just reviewing some results where someone compared results of two binary classification models and the results state that model M1 achieved higher accuracy ...
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1answer
21 views

Data augmentation in deep training

I'm trying to understand the role of data augmentation and how it can affect the performance/accuracy of a deep model. My target application is a fire classification (fire or not, on video frames), ...
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2answers
18 views

Metrics for same signal

Is there a metric in tensorflow.keras.metrics that counts how many time the predicted output and the real output have the same signal? For example, if the ...
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1answer
21 views

Manual way to draw accuracy/loss graphs

During the training process of the convolutional neural network, the network outputs the training/validation accuracy/loss after each epoch as shown below: ...
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0answers
21 views

Advantage of Centralized training in deep learning over distributed training

I know distributed training is the ultimate solution for scalability and solving resource constraints and sometimes distributed training outperforms centralized training in terms of accuracy. But I'm ...
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2answers
18 views

Present results of the best or the last iteration on dev set?

Which is the correct way - presenting the results of the best or the last iteration on the dev set in a paper? In research papers I usually see only one value, is it the best iteration of all? I'm ...
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8answers
6k views

What would I prefer - an over-fitted model or a less accurate model?

Let's say we have two models trained. And let's say we are looking for good accuracy. The first has an accuracy of 100% on training set and 84% on test set. Clearly over-fitted. The second has an ...
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1answer
32 views

Binary Clasification Accurary

newbie speaking: Commonly we can say that accuracy is defined as total positive/ total nbr cases. But I read that, when it is a binary classifier we should consider: TP+TN/ total nbr cases. Can ...
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1answer
24 views

Making sense of a accuracy plot for a 5 fold training using random forest

I'm using sklearn.model_selection.learning_curve for 5 fold training of data. The code is as given below. ...
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2answers
81 views

macro average and weighted average meaning in classification_report

I use the "classification_report" from from sklearn.metrics import classification_report in order to evaluate the imbalanced binary classification ...
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1answer
21 views

evaluation metrics for multiple values per session

I have an application that executes my foo() function several times for each user session. There are 2 alternate algorithms that i can implement as "foo" function and my goal is to evaluate them based ...
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27 views

What will cause high accuracy but a big loss?

In the question of What is the relationship between the accuracy and the loss in deep learning?, @Jérémy Blain gave a fantastic interpretation of 'relationship' between accuracy and loss: 1 - low ...
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1answer
34 views

Keras model evaluation accuracy vs. observation

I am a newbie here and trying to make sense out of the scores from model.evaluate from what I am actually seeing in model.predict...
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1answer
29 views

How can calculate Efficiency for predictive models based on accuracy or error over time?

I was wondering if I could express the efficiency of prognostic models according to their accuracy(error, e.g. MAPE or MSE) over time [sec]. So let's imagine I have the following results for different ...
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1answer
38 views

F1_score(average='micro') is equal to calculating accuracy for multiclasification

Is f1_score(average='micro') always the same as calculating the accuracy. Or it is just in this case? I have tried with different values and they gave the same answer but I don't have the analytical ...
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1answer
54 views

Explanation behind the calculation of accuracy in deep learning model

I am trying to model an image segmentation problem using convolutional neural network. I came across code in Github which I am not able to understand the meaning of following lines of codes for ...
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2answers
50 views

Accuracy of KFold Cross Validation for Neural Network

I have a neural network that Im evaluating using 10 -Fold cross validation. The validation accuracy for a fold changes alot during training in the range of -+10% So for example the validation ...
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2answers
48 views

Classification accuracy based on top 3 most likely classifications

My goal is to recommend jobs to job seekers based on their skill set. Currently I'm using an SVM for this, which is outputting one prediction, e.g. "software engineer at Microsoft". However, consider ...
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2answers
44 views

Classification accuracy of a Random Multi-label Classifier

What is the exact accuracy of a random classifier which has n labels (say 1000) where k labels (say 50) are true? Can I say the accuracy of a random classifier has an upper bound of k/n? -Edit- I ...
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57 views

Prediction error without having a true value

Quick summary about the problem: we are trying to deploy our regression model, where the clients require "individual prediction error". Since we're predicting something unknown in advance, we can't ...
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27 views

Variability in CNN test results

I'm trying to do some time series analysis on 1-minute forex data using a CNN. I'm new to deep learning and just getting started in building a model. So this is probably a very basic question, but I'...
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2answers
126 views

K fold cross validation reduces accuracy

I am working on a machine learning classifier and when I arrive at the moment of dividing my data into training set and test set Iwant to confron two different approches. In one approch I just split ...
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2answers
28 views

Adding extra variables to XGboost model is worsening the train and test accuracy

I am fitting a multi class model using Xgboost. I am getting an accuracy of 96% on Train and 95% on test. I am using the 80-20 train/test split. However, when I am adding two new features , the ...
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1answer
21 views

Can an R^2, or coefficient of determination be used on non-linear data?

I have used the $R^2$ metric to determine how well my neural network performs a non-linear regression. And it seems to work. The plots look almost identical, and I get an $R^2$ value of 0.93... it ...
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1answer
59 views

Building an efficient feature vector

I am building a classifier for malware analysis, which predicts if I have a malware by looking at the intructions of an assembly code, such as push, mov,... and predicting the optimization method. ...
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1answer
32 views

KNN scoring low compared to Logistic regression in MNIST challenge

KNN gives me a score of 0.76100 while it shows 94% accuracy for my training data (splitted with test_size =0.3) in my jupyter notebook while logistic regression gives me a score of 0.91485 with an ...
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1answer
45 views

The loss and accuracy of this LSTM both drop to nearly 0 at the same epoch

I'm trying to train an LSTM to predict the the Nth token using the N-1 tokens preceding it For each One-Hot encoded token, I ...
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4answers
294 views

Confusion matrix - determine the values of FP FN TP and TN

After running my code ,I get the values of accuracy, precision and recall and I want t determine the values of FP FN TP and TN from these metrics. I tried to calculate it using the formula of each ...
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18 views

How could a considerable increase in loss leads to an improvement in accuracy?

I'm experimenting with NLP and at the moment, I'm trying to come up with a translator model for converting English sentences to French counterparts. I'm using this dataset (not that it's relevant): ...
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10 views

Cross_validation is decreasing accuracy?

I have certain dataset to train a model. The dataset is not very small in size. First, I split the dataset into training and validation data using traintestsplit (80-20), train the model on training ...
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22 views

Increase accuracy of occupancy prediction?

I have a project that's aimed to predict the amount of occupants at my local gym given the date and weather. Here's my Kaggle kernel I have two datasets, occupants on a given hour and weather on a ...
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18 views

How to avoid different accuracies when training with subsets?

when trying to train a CNN with randomly selected small subsets (each same size) of the training data set, I get different results in accuracy (the accuracy varies from 0.75 to 0.85). I determine the ...
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53 views

Pytorch testing/validation accuracy over 100%

So I was training my CNN for some hours when it reached 99% accuracy (which was a little bit too good, I thought). But then it didn´t stop and it went higher than 100%. So I thought, that must be ...
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1answer
273 views

Difference of sklearns accuracy_score() to the commonly accepted Accuracy metric

I am trying to evaluate the accuracy of a multiclass classification setting and I'm wondering why the sklearn implementation of the accuracy score deviates from the commenly agreed on accuracy score: $...
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1answer
345 views

sklearn.accuracy_score(y_test, y_predict) vs np.mean(y_predict == y_test)

What is the difference between these two methods for finding model accuracy? I have used both methods in python3 and i normally get identical results. However in few cases i get completely different ...
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1answer
86 views

How to creat a plot for the accuracy of a model

Iam pretty new to the whole topic so please dont be harsh. I know these may be simple questions but everybody has to start somewhere ^^ So I created (or more copied) my first little Model which ...
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117 views

Why does degradation occur in deep neural networks?

It has been shown that "plain" neural networks tend to have an increased amount training error, and accompanied test error, as more layers are added. I am not quite certain as to why this occurs. In ...
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1answer
36 views

CNN for subsets of a dataset - how to tune hyperparameters

I have a dataset and would like to train CNNs on subsets of different size of the dataset. I already have a CNN, which classifies very well if I use the entire dataset. Now the question arises if I ...
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1answer
48 views

Interpreting a curve val_loss and loss in keras after training a model

I am having trouble understanding the curve val_loss and loss in keras after training my model. Can anyone help me understand ...
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1answer
25 views

Sanity check: low PPV but high AUC scores?

I have two algorithms running on a piece of data, both of which perform differently. One of them (call it A) consistently gets a positive predictive value of about 0.75-0.78. Looking at the AUC of ...
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20 views

Binary training result in chainer

I am training simple Chainer based CNN to recognise MNIST samples. To each sample I add poissonian noise. For the test purpose I have always the same random seed. I restart training resetting the ...
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0answers
231 views

Target mean encoding worse than ordinal encoding with GBDT ( XGBoost, CatBoost )

I have a dataset of 23k rows of an unbalanced dataset 85/15 ratio, 10 variables ( 9 of which are categorical ) , i'm using CatBoost and XGBoost for a binary classification. I applied cv (5 iteration ...
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1answer
27 views

How to get the number of steps until a certain accuracy in keras?

I want to see how many steps does it take for my model to reach a certain accuracy.Say 90 percent on cifar10.How can I get this info from the keras model ? EDIT: accuracy in each epoch is accessible ...
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42 views

30% accuracy for training set, 80% for test set with a 0.3 split

I have a time series dataset on which I am training. For some reason, the training accuracy is 30% while the test accuracy is about 88% after about 10 epochs. Is this at all normal? I should point ...
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60 views

test accuracy with tensorflow==2.0.0-beta1 vs TensorFlow version: 2.0.0-alpha0

I am trying run same piece of code on both Tensorflow==2.0.0-beta1 and TensorFlow version: 2.0.0-alpha0 In TensorFlow version: 2.0.0-alpha0 I am getting Test accuracy: 85.08% but on Tensorflow==2.0.0-...
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2answers
57 views

Unable to understand the usage of labels argument in sklearn.metrics.f1_score

I am trying to model a dataset with RandomForest Classifier. My dataset has 3 classes viz. A, B, C. 'A' is the negative class ...