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Questions tagged [classification]

For questions related to the placement of individual cases into categories, such as is essential in fraud detection, spam detection, quality control, prediction of user or market responses, automated organizing or indexing, assigning objects in view to types of obstacles or risks, writing or typing recognition, phonic recognition, .

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11 views

Techniques and semantics in better training of deep learning models

I'm relatively new to Deep Learning, and trying various models and datasets using Keras. I'm starting to love it! Through-out my experimentations, I have come into ...
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1answer
64 views

How can I stabilise a recurrent neural network used for binary classification?

I’m looking for some help with my neural network. I’m working on a binary classification on a recurrent neural network that predicts stock movements (up and down) Let’s say I’m studying Eur/Usd, I’m ...
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1answer
31 views

Classification with deeplearning : clean start vs continue training

I trained some weights to identify apples and oranges (using YOLOv3). If I want to be able to identify peaches, which approach is usually recommended: Start clean and train the 3 classes. Train ...
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1answer
54 views

Grading Questions Using Neural Networks

I have a questionnaire consisting with over 10 questions. The questionnaire is being answered by a lot of people - which I have manually graded. Each question can give the user up to 10 points ...
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1answer
27 views

Semantic issues with predictions made by my trained model

I'm new to Deep Learning. I used Keras and trained a inception_resnet_v2 model for my binary classification application (fire ...
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0answers
19 views

Focal loss for imbalanced multi class classification in Pytorch

I want an example code for Focal loss in PyTorch for a model with three class prediction. My model outputs 3 probabilities. ...
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1answer
929 views

Why is the hyperbolic tangent with MSE better than the sigmoid with cross-entropy?

Usually, in binary classification problems, we use sigmoid as the activation function of the last layer plus the binary cross-entropy as cost function. However, I have already experienced (more than ...
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1answer
115 views

What is the most effective way to build a classifier?

At the moment, I am working on a project which requires me to build a naive Bayes classifier. Right now, I have a form online asking for people to submit a sentence and the subject of the sentence, in ...
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1answer
35 views

What is the best way to find the similarities between two text documents?

I would like to develop a platform in which people will write text and upload images. I am going to use Google API to classify the text and extract from the image all kinds of metadata. In the end, I ...
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1answer
52 views

What are causative and exploratory attacks in Adversarial Machine Learning?

I've been researching Adversarial Machine Learning and I know that causative attacks are when an attacker manipulates training data. An exploratory attack is when the attacker wants to find out about ...
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1answer
46 views

Why does the binary cross-entropy work better than categorical cross-entropy in a multi-class single label problem?

I was just doing a simple NN example with the fashion MNIST dataset, where I was getting 97% accuracy, when I noticed that I was using Binary cross-entropy instead of categorical cross-entropy by ...
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1answer
34 views

How to use a deep learning network on new data-set?

I am trying to use a network for classification. This network works very well on the author's example data, but doesn't work on new data. Currently, I am using the popular EEG Motor Movement/Imagery ...
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1answer
72 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...
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1answer
41 views

How to handle classification with label updates?

Suppose that my task is to label news articles; that is, to classify which category a news article belongs to. Using the labelled data (with old labels) that I have, I have trained a model for this. ...
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1answer
18 views

The best way of classifying a dataset including classes with high similarity?

I have a dataset which has two very similar classes (men wrestling, women wrestling). I've used InceptionV3 as a classifier to solve the problem of classifying this dataset. Unfortunately, the ...
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0answers
13 views

CNN multi output scores and evaluation

I am building a CNN with two outputs. I still have to put time in the network itself, but I was trying to get a good evaluation/classification report of the results. My code is the following: ...
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3answers
4k views

Binary classifier that minimizes false positive error

I have a binary classification problem, where a false positive error has a very big cost compared to the false negative error. Is there a way to design a classifier for such problems (preferably, ...
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0answers
9 views

Is there any time-varying directed graph dataset?

I am interested in the node classification task for graph data. So far,I've tried it with the Cora dataset, but it is an undirected graph and has word attributes as features. I want to extend this ...
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4answers
1k views

What makes neural networks so good at predictions?

I am new to neural-network and I am trying to understand mathematically what makes neural networks so good at classification problems. By taking the example of a small neural network (for example, ...
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2answers
493 views

How does text classification reduce manpower costs?

(I apologize for the title being too broad and the question being not 'technical') Suppose that my task is to label news articles. This means that given a news article, I am supposed to classify ...
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1answer
59 views

Does a data structure that models the encoding specificity principle in memory exist?

I find myself wondering if there exists a data structure with the following properties: Stores information Conforms to the encoding specificity principle
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2answers
93 views

How do we know the classification boundaries of the data?

Consider an image classification problem. Conceptually, we then have some high dimensional space where all the images can be represented as points, and having large enough labeled data set we can ...
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1answer
79 views

Using AI to interpret the nature a specific input and use the correct model

How would one go about building an AI that is capable to look at any kind of input and then identify what is the nature of this data? For example, an AI that is able to do image classification, NLP ...
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1answer
36 views

Is there any measure of separability of classes?

I want to know if there is a measure of how well two classes in Y are separable (linearly or not) based on their features in X. Easiest way of explaining this is to compare it to correlation ...
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1answer
49 views

How do I determine the most appropriate classifier for a certain problem?

Consider a Bayesian classifier used in spam e-mail filtering. It converts an e-mail to a vector, most of the time using the bag-of-words method. Although it learns first before getting employed, it ...
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1answer
20 views

Are there deep networks that can differentiate object class from individual object?

We usually categorize objects in a hierarchy of classes. Let us say crow vs bird. In addition, classes can be "messy", for instance a crow can be also a predator, but not all birds are predators. My ...
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1answer
33 views

Why is image classification tasks are dominated by minimizing cost function instead of maximizing ones?

I was watching a video of policy gradient by Andrej Karpathy at 10:00 there shows an equation for supervised learning for image classification. $max\sum _{i}log \:p(y_i|x_i)$ I have worked with ...
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1answer
32 views

Maximum Likelihood Classifier vs. Bayesian Network

I am confused in understanding the Maximum Likelihood as a classifier. I know what is Bayesian network and I know that ML is used for estimating the parameters of models. Also, I read that there are ...
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1answer
64 views

Should I use single or double view for gender recognition?

My project requires gender recognition of people shown on the given images, with more than one person per image. However, these people can be positioned in frontal or side view(passing by ...
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1answer
48 views

TF Keras: How to turn this probability-based classifier into single-output-neuron label-based classifier

Here's a simple image classifier implemented in TensorFlow Keras (right click to open in new tab): https://colab.research.google.com/github/tensorflow/docs/blob/master/site/en/tutorials/quickstart/...
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0answers
15 views

Trying to separate spiral data with neural network, learning tensorflow

I am learning how to use tensorflow without keras, just to make sure I understand tensorflow directly. I created a spiral-looking datasets with 100 points of each class (200 total), and I created a ...
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0answers
59 views

What to do when an image classifier does good for a class but bad for another?

So I wrote a convolutional neural network for a binary image classification. I have around 5300 images for each class which I thought would be enough to at least give me a good accuracy on the ...
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2answers
140 views

Measuring and Classifying human intelligence?

I have a dataset of millions of chat messages from different discussions. Some of the messages are written by people who lack understanding or relevant language skills. These messages almost always ...
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1answer
497 views

Loss function for Hierarchical Multi-label classification

I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels like multilayer perceptron ( MLP )branch ...
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3answers
120 views

Feature Selection algorithm for a high featured data

I have a cancer patient database from mass spectrometry on patients which consists of more than half million features. My task is to apply a feature selection algorithm to extract the most relevant ...
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1answer
43 views

Can a model, retrained on images classified previously by itself, increase its accuracy?

Let's assume I have a CNN model trained to categorize some objects on the images. By using this model I find more categorized images. If I now retrain this model on data set that consists old set and ...
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0answers
7 views

Fusing label distribution and on-hot encoded labels

A while ago I came across a paper for image classification that utilized both label distribution and one-hot encoded labels to classify images. An image has a label distribution for all classes (4 ...
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1answer
20 views

How to change this RNN text classification code to become text generation code?

I can do text classification with RNN, in which the last output of RNN (rnn_outputs[-1]) is used to matmul with output layer weight and plus bias. That is getting a word (class name) after the last T ...
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1answer
95 views

Detecting playing cards with a neural network

I want to train an AI to detect playing cards. For that reason I bought many different decks, scanned and labeled them. Next up would be to create training data with an augmentation library. I found ...
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1answer
47 views

Relationship between input range and channel means, standard deviations for CNNs

So, I'm using a pretrained pnasnet5large model to do some image classification (https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/pnasnet.py) In the file, it ...
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0answers
33 views

Indian Traffic Sign Dataset

I am looking for the Indian Dataset of traffic signs. There is a dataset developed recently IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environments which contains ...
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0answers
15 views

Probabilistic classification - normalize results

I have a probabilistic classifier that produces a distribution over my 3 classes - C1, C2, C3. I want to compare some new points I'm classifying to each other, to see which one is the best fit for a ...
2
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1answer
50 views

Video engagement analysis with deep learning

I am trying to rank video scenes/frames based on how appealing they are for a viewer. Basically, how "interesting" or "attractive" a scene inside a video can be for a viewer. My final goal is to ...
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2answers
247 views

Is there a way to classify sounds

To classify images we are using the tensorflow incection v3 NN. Is there a similar approach to classify sounds? As for example to be able to recognize the person who is talking or classify a general ...
3
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2answers
133 views

Why not use the MSE instead of the current logistic regression?

When watching the machine learning course on Coursera by Andrew Ng, in the logistic regression week, the cost function was a bit more complex than the one for linear regression, but definitely not ...
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1answer
43 views

Is there a theory behind which model is good for a classification task for the convolutional neural network?

Let say I'm trying to apply CNN for image classification. There are lots of different models to choose and we can try an ensemble, but given a limit amount of resources, it does not allow to try ...
3
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1answer
90 views

Can I train a neural network incrementally given new daily data?

I would like to know if it was possible to train a neural network on daily new data. Let me explain this more in detail. Let's say you have daily data from 2010 to 2019. You train your NN on all of it,...
5
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2answers
69 views

Two data classes for a convolutional neural network, can one have a LOT more images for training than the other?

I have two classes in the training set: one that has images with a feature and the other of images without that feature. Can there be a LOT more images with "no feature" so I can fit in all possible ...
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1answer
20 views

Solution to classify product names

I have a bunch of training data for classifying product names, around 30,000 samples. The task is to classify these product names into types of product, around 100 classes (single words). For example:...
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1answer
38 views

TensorFlow estimator DNNClassifier fails to fit simple data

The ready-to-use DNNClassifier in tf.estimator seems not able to fit these data: ...