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Questions tagged [accuracy]

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1answer
31 views

Can `k=1` be a good choice for K neighbors classification?

Running sklearn.KNeighborsClassifier() on Kaggle's Leaf Classification sample (set of 99 species, 10 specimen each), with defaults kNN parameters and a grid search ...
0
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1answer
21 views

How to compare two sets of class frequency data?

I am working with a machine learning approach that counts 2 classes of objects in images: people and cars. I have a predicted dataset, which is the predicted output from the machine learning approach ...
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2answers
49 views

loss/val_loss decrease but acc/val_acc are persistence

I don't know why do I get such fantastic result? Epoch 3/10 2937/2937 [==============================] - 12s 4ms/step - loss: 0.2836 - acc: 0.4679 - val_loss: 0.1937 - val_acc: 0.1980 Epoch ...
7
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3answers
310 views

Inverse Relationship Between Precision and Recall

I made some search to learn precision and recall and I saw some graphs represents inverse relationship between precision and recall and I started to think about it to clarify subject. I wonder the ...
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2answers
52 views

loss/val_loss are decreasing but accuracies are the same in LSTM!

I am trying to train a LSTM model, but the problem is that, the loss and val_loss are ...
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2answers
42 views

Classifier performance evaluation

I have an unbalanced dataset which has 920 samples in total, 689 belong to the first class, and 222 to second class. and both classes are significant for me. so when building a classifier model such ...
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0answers
25 views

CNN accuracy and loss doesn't change over epochs for sentiment analysis

I am performing text classification as Good [1] or Bad [0]. The texts are preprocessed and converted to Vectors using Google Word2Vec. Further CNN architecture is used for training. I have roughly ...
1
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1answer
23 views

Accuracy after selftraining didn't change

I used Decisiton Tree Classifier which I trained with 50 000 samples. I have also set with unlabeled samples, so I decided to use self training algorithm. Unlabeled set has 10 000 samples. I would ...
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0answers
22 views

CNN validation accuracy not improving - spectrogram

I am new to Machine Learning. So, for a project I am trying to classify instruments in .wav file. The dataset I am using is IRMAS. Dataset contains 11 classes of instruments with recordings in 16 bit ...
7
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2answers
388 views

Validation vs. test vs. training accuracy. Which one should I compare for claiming overfit?

I have read on the several answers here and on the Internet that cross-validation helps to indicate that if the model will generalize well or not and about overfitting. But I am confused that which ...
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0answers
29 views

how to interpret categorical cross entropy and categorical accuracy

When evaluating a multi-class model, How to interpret / identify that your model is performing accurately or works well with the categorical cross entropy and categorical accuracy values? I am ...
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1answer
24 views

Can this be a case of multi-class skewness?

I have been working on an email data set, and trying to predict the owner team for it. But my prediction accuracy is just 58%. I have implemented data cleansing, null value removals, duplicate removal,...
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1answer
33 views

Keras: extreme spike in loss during training

I am training an LSTM for time series forecasting and it has produced an extremly high loss value during one epoch: ...
2
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1answer
31 views

Why is my training accuracy decreasing higher degrees of polynomial features?

I am new to Machine Learning and started solving the Titanic Survivor problem on Kaggle. While solving the problem using Logistic Regression I used various models having polynomial features with ...
1
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1answer
173 views

Best CNN architecture for binary classification of small images with a massive dataset [closed]

The title has it all... Any tip is welcomed. Should I use a very deep convolutional neural network ? Use a large amount of filters ? Parallel layers ? Dataset examples: 1) "Good" 2) "Bad"
1
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1answer
37 views

How do data scientists test the claimed accuracy of a model?

For example, if you are a data scientist at a company, and a salesperson offers you a pre-trained model that is claimed to have a 90% accuracy of detecting fraudulent transactions. How would you go ...
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0answers
15 views

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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0answers
22 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 ...
1
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1answer
21 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 ...
1
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1answer
14 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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0answers
12 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 are used to improve the accuracy of a single tree methods such as C4.5 but applying both of them over the same dataset I got better accuracy with C4.5, ...
2
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1answer
14 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 ...
2
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2answers
64 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
54 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 ...
1
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1answer
56 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
75 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
67 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?
1
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1answer
61 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 ...
1
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1answer
32 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 ...
0
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1answer
26 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: ...
1
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1answer
26 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
82 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
49 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 ...
2
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1answer
362 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
43 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 ...
0
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1answer
985 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
4
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1answer
286 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
199 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
797 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 ...
2
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2answers
62 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 ...
1
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1answer
36 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 ...
2
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0answers
151 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
10 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). ...
1
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1answer
33 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 ...
1
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1answer
42 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 ...
2
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2answers
69 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
638 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
31 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
52 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 ...