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Questions tagged [accuracy]

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33 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
12 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
15 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
33 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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20 views

How to calculate accurate values of parameters if I know the formula's form and many of its samples with python?

If we know a formula's form, but don't its parameters, E.g. y = a*(x1**3)+b*(x2)+c*(x3) I don't know the a, b, c, but I'm sure the variables of x1, x2, x3 and y's relationship should follow this ...
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17 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
104 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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0answers
15 views

How to evaluate accuracy for a multiclass classification algorithm which creates its own classes?

I have a classification algorithm, which (very) regularly sees data which is not part of any previously seen classes and must create a new class, which future data could be classified into. How should ...
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1answer
44 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
147 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
138 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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1answer
34 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
31 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
44 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
7 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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0answers
54 views

Metric to evaluate keras multi-class text classifiation

I saw a lot of published jupyter notebooks where a multi-class text classification was performed. In most cases there are more than 3 possible classes. However, I noticed that the models usually 'only'...
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1answer
27 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
22 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
33 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
34 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
249 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
28 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 ...
3
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1answer
39 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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2answers
26 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 ...
1
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1answer
22 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
50 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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0answers
30 views

Train the model to increase accuracy rather than to minimise loss

I am currently in a situation of seq2seq training where the cross entropy loss is very low (near zero) but the accuracy is also very low. This made me wondering if there were any loss functions that ...
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0answers
9 views

Convolutional network instability

Depending of the starting weights, my CNN have very different results, from a 90% accuracy on test set to not learning at all. Is there something I can do to adress that apart setting a random seed?
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6answers
1k 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
92 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
75 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
50 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 ...
17
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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
767 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
236 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
950 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 ...
3
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0answers
182 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: ...
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0answers
33 views

Optimize F-Score only for certain classes, disregard other classes

I have a labeled dataset of product reviews where the label is a rating between 1 and 5 and the review is just text. I use a simple naive Bayes classifier (sklearn) to try to predict a rating given a ...
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1answer
265 views

Calculate average Intersection over Union

I want to have a global IoU metric for each class in a segmentation model with a neural net. The idea is, once the net is trained, doing the forward pass over all training examples an calculate the ...
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3answers
1k views

How to improve accuracy of deep neural networks

I am using Tensorflow to predict whether the given sentence is positive and negative. I have take 5000 samples of positive sentences and 5000 samples of negative sentences. 90% of the data I used it ...
4
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1answer
499 views

Which Loss cross-entropy do I've to use?

I'm working with this dataset https://www.kaggle.com/c/sf-crime to predict the crime incident using keras. I've encoded the category with pd.get_dummies and then use it as the validation data. At ...
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1answer
84 views

Very low accuracy of new data compared to validation data

I'm trying to train the neural network to predict the movement of a particular security on the market. I teach on historical data collected for the year. At the entrance of the neural network ...
0
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1answer
39 views

How can we create neural net to detect false predictions?

I created a convolutional network to recognise certain substrings. For example, the following phrases would be mapped to the "What" class: ...
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3answers
2k views

How to improve loss and avoid overfitting

I'm trying to build a 2 class image classifier using the architecture suggested in first part of this blog https://blog.keras.io/building-powerful-image-classification-models-using-very-little-data....
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1answer
235 views

trying to decrease overfitting with regularisation in CNN

I am doing transfer learning by retraining the publicly available inception layer, without regularisation here are my initial parameters and results: ...
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2answers
155 views

What makes you confident in your results? At what point do you think you can present your work to tech illiterate superiors?

I understand that the models are only as good as the data you get, and bad design can generate really bad data. Nonrandom sampling, unbalanced/incomplete designs, confounding, can make data analysis ...
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1answer
34 views

How to separate overlapping curves more effectively?

So, I am trying to create a Neural Network which will effectively separate 2 Gaussian curves with somewhat different means and standard deviations. My basic aim is, for some given input vector the ...
0
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1answer
192 views

different results with MEKA vs Scikit-learn!

I have a multilabel data which I've trained using different classifiers with MEKA (multilabel version of WEKA) and the evaluation results (e.g. accuracy) that MEKA gives me are different from those I ...
0
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1answer
53 views

Reason for having both low loss and same predicted class?

I'm training a cNN for binary classification. I used a batch size of 128, and the loss is decreasing and accuracy is increasing over epoches. The accuracy reached over 0.99 eventually, and the loss ...
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2answers
173 views

Matrix Confusion - Get Model Precision

I've this matrix confusion: [9779 107] [2227 148] What is the accuracy of my model? My doubt is because the confusion matrix is calculated based on Test ...