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Questions tagged [accuracy]

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Different testing and training accuracy values within a NN TensorFlow structure

In order to select the optimum number of my gradient descent algorithm, I had used a for loop of 1500 iterations and each 100 iterations training and testing accuracies are printed. Here everything is ...
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16 views

Regression model Giving the same prediction for all new inputs until i load the model again

I have build a regression model that has some decent accuracy measures. I have pickled it and loading it another project. However it is producing the same predictions every time when i pass new ...
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1answer
15 views

Autoencoder doesn't learn to reduce dimesions

I coded a neural network from scratch in Python. I tried it with the XOR problem and it learned correctly. So I tried to encode an Autoencoder with 3 inputs (and therefore with also 3 outputs) to ...
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1answer
6 views

My accuracy changes throughout every epoc but the val_acc at the end of each epoc stays the same

I am training a transfer learning CNN on 161 pictures that have been augmented into 966 photos, 4 classes. I am training on a balanced data set, so there are 52 images of each class and also in the ...
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7 views

Is it possible to have a better performance with C4.5 than Bagged tree?

I am not sure but I have read that bagged trees is used to improve the accuracy of a signle tree methods such as C4.5 but applying both of them over the same dataset I got better accuracy with C4.5, ...
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18 views

Visualization decision tree [closed]

Run into problem when i visualizing decision tree here is the code: ...
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1answer
9 views

How should multiclass classifier performance be measured when one type of error is preferred over another?

Sorry if this question has been asked before--I am having trouble searching this topic since I'm not sure of my wording. Say you have a classification problem where there are more than two labels ...
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14 views

Data Set with more than 800 obs and more than 20 features to compare MLmodels accuracy [migrated]

I'm looking for a data set (ideally a csv file) that contains more than 800 obs and more than 20 variables statistically significant to compare nearest neighboors, linear/logistic models, penalised ...
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2answers
48 views

Accuracy differs between MATLAB and scikit-learn for a decision tree

Is there any possibility to vary the accuracy of same data set in matlab and jupyter notebook by using python code ? For same data set, at first I applied it in matlab and get 96% accuracy for ...
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1answer
20 views

Metrics for presenting RNN/LSTM result

I am working on a two different architecture based on LSTM model to predict the users next action based on the previous actions. I am wondering, what is the best way to present the result? Is it okay ...
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1answer
29 views

Confidence Score For Trained Sentiment Analyser Model

I have trained a text based sentiment analysis model, using SciKit-learn and custom data. I have the model ready and it works fine in predicting a text to a class (Positive or Negative or Neutral). I ...
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2answers
72 views

How can I know if my NN TensorFlow model is overfitted or not?

I am new with TensorFlow (Python) and I can not juge my obtained results in terms of training and testing accuracy I am using the GradientDescentOptimizer with a learning coeff equal to 10^(-4) and ...
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2answers
66 views

How can I check if a bigger training data set would improve my accuracy of my scikit classifier?

How can I check if a bigger training data set would improve my accuracy of my scikit classifier, is there a method or something?
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1answer
25 views

test accuracy of text classification is too less

I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G].I have 13 examples for each class. I preprocessed the subtitles in the following ...
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1answer
29 views

Performance of model in production varying greatly from train-test data

I was wondering if anyone has any advice on where to start digging for this problem. I have a model which has gone through development and all train/cv/test data sets now perform above 95% both for ...
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1answer
22 views

My training accuray is 1.0 but the predictions on the training data are wrong

My neural network is not working right, and I am trying to find out what is up. I inserted just three images to a transfer learning (mobilenet) neural network. The three images' classes are: array([[...
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0answers
19 views

Why is my model not learning and the accuracy varying wildly? How can I smooth out these issues?

I'm trying to predict from initial trade terms whether a trade will be rejected, accepted, or abandoned. Here are the stats for the training set and the test set: Training: ...
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1answer
24 views

How can we show that one model might have higher accuracy than another model but at the same time lower AUC?

Assume that we have two classification models M1 and M2 that are evaluated on five test instances. How to show with an example that M1 can have a higher accuracy than M2, while at the same time M2 has a ...
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2answers
53 views

Validation accuracy is always close to training accuracy

I am trying to tune the hyperparameters of a LSTM I have to do time series forecasting. I have noticed that my validation accuracy is always very close to my training accuracy. I am not sure whether ...
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0answers
27 views

How do I perform Leave One Out Cross Validation For Top n Recommendation Sytems?

I am new in making recommendation systems . I am using the surpriselib library to evaluate my recommendations. All the Accuracy Metrics are well supported in this library. But I also want to compute ...
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1answer
122 views

human level performance on ImageNet, top-1 or top-5?

Anyone have pointers to where the human level performance on ImageNet comes from? I found a reference to 5.1% accuracy (top-1? or top-5?) from here.
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2answers
41 views

Deep Learning Network decreasing in accuracy

In order to familiarize myself with semantic segmentation and convolutional neural networks I am going through this tutorial by MathWorks: Semantic Segmentation Using Deep Learning I did not use the ...
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40 views

multiple hypothesis testing in machine learning

I am working with a dataset with multiple measurements at different time points, and outcomes at each time point. I have been asked by my supervisor to predict the outcomes at later timepoints using ...
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1answer
424 views

Accuracy for Kmeans clustering

I am looking for accuracy python code for kmeans clustering with no labels. Is there anyone who knows about it? it is ok that is not built-in function. Manually made is also ok
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1answer
111 views

What is the classification accuracy of a random classifier?

I have a build a classification model using machine learning technique (SVM). I want to compare the classification accuracy of my model with a random classifier. My data set contains only two classes(...
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4answers
161 views

Metrics to determine K in K-cross fold validation

Consider a scenario where the dataset in hand is quite large, let's assume 50000 samples (quite well balanced between two classes). What metrics can be used to decide the K value in a K-fold cross-...
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3answers
356 views

Keras LSTM accuracy stuck at 50%

I'm trying to train an LSTM for sentiment analysis on the IMDb review dataset. As input to the word embedding layer, I transform each review to a list of indices (that corresponds to word index in ...
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2answers
51 views

Logloss vs Accuracy. Which needs to be chosen to evaluate the model performance

While model tuning using Cross validation and Grid search , I was plotting the graph of different learning rate against logloss and accuracy separately. Graph of Logloss --> learning Rate When I ...
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1answer
34 views

How can we use machine learning to distnguish between similarly looking images

How can I build a model which can distinguish between Milk and Phenyl? I want to predict whether a given item is edible to eat or not. If I train a model with thousands of photos of Milk and Phenyl ...
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0answers
103 views

Hands on Machine Learning with Scikit Learn and TensorFlow Confusion Matrix with VERY BAD score [closed]

I followed the steps EXACTLY in the Hands on Machine Learning with Scikit Learn and TensorFlow ch. 3. But the confusion matrix for the multinomial classifier is very very bad. Even though the book ...
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0answers
8 views

Validating performance of panel data based models

I'm wondering from a theoretical/general practice perspective, what is the best way to evaluate performance of regression models derived from panel data (i.e. a time series of cross sectional data). ...
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1answer
29 views

Why not higher accuracy in Otto data?

On this site of Otto Group Product Classification Challenge, it is shown that best accuracy was possible with RandomForest method, but it was relatively low at 0.83. Accuracy with ANN and with Naive ...
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0answers
23 views

Why different results on repeated runs

I find that if I run my convolution neural network repeatedly on same data, I get train accuracy varying from 5% to 95%. Is this common or usual? What could be causing it and how can it be reduced? ...
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1answer
39 views

Target data values are not evenly distributed

Data nature: I have features with 10 numeric type, and other 10 categorical, with a lot of values, at the end, using one-hot encoding I got a matrix of 600 columns. My problem is with accuracy ...
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2answers
51 views

Interpretation of accuracy score on subset of data points

I have a multi-class problem that I am building a classifier for. I have N total data points I would like to predict on. If I instead predict on n < N data points and get an accuracy score, is ...
2
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1answer
469 views

0.1 accuracy on MNIST fashion dataset following official Tensorflow/Keras tutorial

My goal is to classify products pictures into categories such as dress, sandals, etc. I am using the MNIST fashion dataset, following this official tutorial word-per-word: https://www.tensorflow.org/...
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2answers
29 views

AUC is high but not able to represent other class properly

I wanted to know if it makes sense to make 2 ROC curves for each of the 2 classes? I am doing a binary classification problem but AUC is good at 82%. But the F Score of the class labelled 1 is very ...
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1answer
48 views

How to interpret my neural network with high accuracy but low probability in test results

I have built a classical ANN using keras which provides probability (using sigmoid function) of the outcomes (0 or 1). While the accuracy of the model is high when the model is fit ~90%, the outcome ...
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3answers
31 views

which of stable training results or good test results is more important?

which of stable training results or good test results are more important? For instance obtaining an unstable training accuracy in different episodes but good test accuracy is better or obtaining a ...
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1answer
32 views

How to interpret a drastic accuracy loss while training a neuronal net (CNN)?

How can one interpret a drastic accuracy loss after ~38 epochs? Maybe more dropout should be added to the CNN network? (x-axis shows the number of epochs)
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2answers
92 views

What is the highest accuracy for classifying cats and dogs from CIFAR-10?

Resnet, DenseNet, and other deep learning algorithms achieve average accuracies of 95% or higher on CIFAR-10 images. However, when it comes to similar images such as cats and dogs they don't do as ...
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6answers
2k views

I got 100% accuracy on my test set,is there something wrong?

I got 100% accuracy on my test set when trained using decision tree algorithm.but only got 85% accuracy on random forest Is there something wrong with my model or is decision tree best suited for the ...
0
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1answer
158 views

Titanic Kaggle Data: Why am I getting lower accuracy on Kaggle submissions than on held-out data?

I am going through my first solo machine learning project and would like to gain some insight into what I am doing wrong/what is going on here as I am a bit stuck. I have been applying machine ...
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1answer
83 views

Is it possible to find a model that minimises both false positive and false negative?

Is it possible to come up with a model that minimises both false positive and false negative? Minimising can be done to a point, such as the Bayes error threshold.
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1answer
58 views

Confusion regarding classification accuracy calculation and result

The total number of data points for which the following result is obtained = 1500. Out of which, I have 1473 labelled as 0 and the remaining 27 as ...
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4answers
3k views

Is it always better to use the whole dataset to train the final model?

A common technique after training, validating and testing the Machine Learning model of preference is to use the complete dataset, including the testing subset, to train a final model to deploy it on, ...
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2answers
1k views

Classification Accuracy in Keras

I'm using two different functions to calculate the accuracy of my deep learning model and I am confused which one is which. The first one is ...
3
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2answers
404 views

Why validation loss worsens while precision/recall continue to improve?

I'm training a neural network on 'easy' dataset with ~15k examples. Network overfits pretty fast. The thing I cannot understand that after 5th epoch validation loss is starting to worsen, while ...
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4answers
2k views

In which epoch should i stop the training to avoid overfitting

I'm working on an age estimation project trying to classify a given face in a predefined age range. For that purpose I'm training a deep NN using the keras library. The accuracy for the training and ...
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0answers
233 views

Validation score (f1) remains the same when swapping labels

I have an imbalanced dataset (True labels are ~10x than False labels) and thus use the f_beta score as a metric for model performance, as such: ...