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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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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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10 views

Embedding Gensim fast-text

Would you suggest to train my own Fast-text embedding using the Gensim library despite i have 1800 sentences and 2k vocabulary length? Don't you think there are too few words? or is there not a ...
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Evaluation metrics multi-class classification (ROC- PR curves)

Facing with a multi-class classification task, my question is: are ROC and Precision-Recall (One-vs-All-Rest) curves useful to evaluate and visualize the performance of a model? or Confusion ...
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Classification of classes within meta-classes

TLTR: I'm developing a CNN for a classification task. The data contains multiple classes some of which are very similar to each other and I know these meta-classes. In such a situation is it a good ...
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0answers
18 views

When to use which metric in machine learning?

In machine learning, there are several metrics to assess the quality of the models: accuracy, precision, recall, f measure, ROC (AUC), etc. There are cases when certain metrics are more appropriate ...
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2answers
68 views

How do I improve accuracy and know when to stop training?

I am training a modified VGG-16 to classify crowd density (empty, low, moderate, high). 2 dropout layers were added at the end on the network each one after one of the last 2 FC layers. network ...
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0answers
24 views

Can we compare MAE MSE results with categorical_crossentropy?

can i compare MAE and MSE loss results of a regression CNN with categorical_crossentropy loss of a classification CNN if they both have similar tasks? is yes how to?
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Why validation performance is unstable for my LSTM based model (labelling problems)?

I have trained a recurrent neural network based on 1 stack of LSTM cells. I use it to solve a classification problem. The RNN cell has 48 hidden states. The output of the last unfolded LSTM cell is ...
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23 views

metrics evaluation multiclass classification

I am working on intent classification task (chatbot engine), 2k sentences, 24 classes. Major class is composed of about 150 sentences, minor class of about 35 sentences, the others are more or less ...
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24 views

Is making lot of 1 versus other model efficient?

I've got classification problem on image, I have 10 classes and when I fine tuned my model on it (I tried VGG, Xception, resnet etc) I have approximatly 83% validation accuracy. I was wondering if ...
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1answer
34 views

Why don't we perform classification of crowd density?

For the case of crowd density estimation using CNN, using datasets like shanhaiTech or UCF, why there hasn't been attempts to tackle this type of task as a classification problem? All current papers I'...
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1answer
54 views

Why doesn't my image classification network get better with training?

I am attempting to train a network to do something I thought would be a relatively simple case to learn with: identify whether the back of a scanned vintage postcard has one of 'no postage stamp', a '...
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1answer
50 views

Multi class text classification with imbalanced data

I am dealing with intent classification task on an Italian customer service data set. I've more or less 1.5k sentences and 29 classes (imbalanced). According to the literature, a good choice is to ...
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14 views

Siamese Network for unknown object

I am currently trying to create a One-Shot network using the Siamese architecture for an object that isn't a face. My problem is, in normal Face Recognition the detecting gadget (e.g. Smartphone) ...
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1answer
27 views

How much the dialects recognition and speech recognition are relevant?

In this tutorial, they build a speech recognition model to classify a one-second audio clip as one of ten predefined words. Suppose that we modified this problem as the following: Given an Arabic ...
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1answer
40 views

What should the range of the output layer be when performing classification?

I am working on a MLP neural networks, using supervised learning (2 classes and multi-class classification problems). For the hidden layers, I am using $\tanh$ (which produces an output in the range $[...
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0answers
63 views

Dialects classification using deep learning

Dialects differ a lot between cities in my country, Syria. People sometimes express themselves using different local phrases and idioms which refer to the same topic. So, I came up with the idea of ...
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19 views

identifying pattern in datasets

i am new to machine learning. i'm trying to identify driving pattern through accelerometer and gyroscope sensor. i have been collecting the data of both the sensors and have been storing them in .csv ...
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1answer
11 views

Using convnet to classify language of text contained in images

I hope this question is not too broad or general. I have a very large set of images all of which contain text (some have more, some less). All of them have been tagged as containing, say, English text ...
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1answer
31 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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19 views

Any guidance on learning rate / batch size for noisy data (high Bayes error rate)?

Is there any guidance available for training on very noisy data, when Bayes error rate (lowest possible error rate for any classifier) is high? For example, I wonder if deliberately (not due to memory ...
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2answers
66 views

Is there a way to understand the type of a sentence?

I am a beginner, just started studying around NLP, specifically various language models. So far, my understanding is that - the goal is to understand/produce natural language. So far the methods I ...
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0answers
20 views

Bubble Chamber Image Analysis Using Neural Network

I have a data analysis problem that I can reduce to one similar to analyzing the trajectories in the images below. These images show the tracks of subatomic particles interacting in a bubble chamber. ...
2
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1answer
53 views

Text classification task chatbot

I'm building a customer assistant chatbot in Python, so a text classification task, and I have available more or less 7 hundred sentences of average length 15 words (unbalanced class). What do you ...
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1answer
55 views

How do I classify measurements into only two classes?

I am a member of a robotics team that is measuring the amount of reflected IR light to determine the lightness/darkness of a given material. We eventually hope to be able to use this to follow a line ...
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0answers
13 views

Property based clustering

I've got a challenge that feels like it should be solvable using some kind of clustering algo, but I can't get my head around how I can change the perspective such that it is solvable for such an algo....
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1answer
17 views

Natural language recommendation system: to pre-classify inputs or not?

Does it help to "pre-classify" natural language inputs using labeled input fields? E.g., "Who," "What," "Where," "When," "Why," "How," and "How much?" Or is a single, monolithic, free-form, long-text ...
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2answers
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Can machine learning algorithms (CNNs?) be used/trained to differentiate between small differences in details between images?

I was wondering if machine learning algorithms (CNNs?) can be used/trained to differentiate between small differences in details between images (such as slight differences in shades of red or other ...
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2answers
42 views

Will a neural network always predict the correct label if it sees the exact same input during training and testing?

If I'm performing a text classification task using a model built in Keras, and for example, am attempting to predict the appropriate tag given a Stack Overflow question: "how to subtract 1 from an ...
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1answer
57 views

Why is the last layer of a DBN or DBM used for classification task?

I understand why deep generative models like DBN ( deep belief nets ) or DBM ( deep boltzmann machines ) are able to capture underlying structures in data and use it for various tasks ( ...
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2answers
115 views

Can neural networks learn to ignore an input datum?

Disclaimer: I'm not a student in computer science and most of my knowledge about ML/NN comes from YouTube, so please bear with me! Let's say we have a classification neural network, that takes some ...
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1answer
27 views

Beginner - Object classification data in a neural network

Imagine I wish to classify images of digits from 0-9. Let's say I have trained the network to recognise '1'. If I were to train the same network to recognise '2', wouldn't the backpropagation process ...
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1answer
2k views

TypeError: 'numpy.ndarray' object is not callable

I was trying to implement CapsuleNet for classifying some of the Native digits. All the images are RGB images and resize to ...
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1answer
37 views

Python Network for Simple Image Classification

I'm wondering if there exists a network for simple image classification. What I mean by this is if I have two image datasets, one of horses and one of zebras, I want to train off the horses and ...
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1answer
25 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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2answers
91 views

What is the difference between imitation learning and classification done by experts?

In short, imitation learning means learning from the experts. Suppose I have a dataset with labels based on actions of experts. I use a simple binary classifier algorithm to assess whether it is good ...
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0answers
38 views

Machine learning approach to facial recognition

First of all i'm very new to the field. maybe my question is a bit too naive of even trivial.. I'm currently trying to understand how can i go about recognizing different faces. Here is what i tried ...
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1answer
36 views

Using unsupervised learning for classification problems

Let's say there are two types of cancer(Type 1 and Type 2). Say we want to see if one of pour friends has cancer Type 1 or 2. We can treat this as a classification problem. But what if we use ...
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1answer
33 views

Doubts at basic step of learning problem

Question: Express each of the following tasks in the framework of learning from data by specifying the input space X, output space Y, target function f:X->Y and the specifics of the data set that we ...
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2answers
114 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
36 views

Class Restriction in Generative Adversarial Networks

this is my first post here. Our problem setting: We have to do a binary classification of data given a training-dataset D, where the majority of items belongs to class A and some items belong to ...
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1answer
40 views

Influence of location on a Neural Network trained for parking detection occupancy

I loaded a neural network model trained with Caffe by other people in OpenCV. The model should detect the presence of a car in a single parking spot outputting the probability of it being free/...
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0answers
54 views

Variable sized input-Multi Label Classification with Neural Network

I have a data input vector ( No Image classification) which size varys from 2 to 7 entrys. Every one of them belongs to a class Out of 7. So I have a variable Input size and a variable Output size. ...
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1answer
29 views

Recognising Noise in Simple Classification

I have created a classifier for some simple gestures using an input layer, a hidden layer with tanh activation and an output softmax layer, I'm also using the Adam optimiser. The network classifies ...
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1answer
47 views

How to define a loss function for a classifier where the confusion between some classes is more important than the confusion between others?

I have a dataset of images belonging to $N$ classes, $A_1, A_2...A_n,B_1,B_2...B_m$ and I want to train a CNN to classify them. The classes can be considered as subclasses of two broader classes $A$ ...
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2answers
498 views

Keras : get back labels from a model

I have a saved keras model. How can I get back the labels from the model ? Because right now, I can use the predict method to get back the probability for a sample to belong to a certain class e.g. ...
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0answers
14 views

Merge one label with one information for classification problem or multi-label classification

I want to build a model to support decision making in order to propose or not loan insurance to clients. Because sometimes clients asking loan and loan insurance have less chance to have their loan ...
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4answers
119 views

Using Convolutional Neural Networks for movement classification

I have programmed my first network for the MNIST dataset. I was wondering what the first approach would be to recognize certain movements. I have read about that the time dimension should be ...
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1answer
41 views

How does an svm work? How does it perform comparisons between malignant and benign tumor

How do Support Vector Machines (SVMs) differentiate between a glass and a bottle or between a malignant and a benign tumor when it dealing with it for the first time? What will be the analysis ...
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1answer
81 views

Using 3D Points as Inputs to a Neural Net

I am currently looking to use a neural network to classify gestures. I have a series of Dx,Dy,Dz readings that represent the differences across the three axes made during the gesture. About 10 ...