Questions tagged [classification]

An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.

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Any there databases with native support for applying a NN model to produce search rankings?

The Situation: I have a simple neural net with an input vector that consists of the euclidean distance between the attributes of two cars. (For example the attributes would include wheel size, car ...
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Precision of quantized MobileNet v1 224 on CPU and Edge TPU

I am using a quantized MobileNet model for inference tests. I use an Coral Edge TPU and my CPU. For the Edge TPU I use the class ClassificationEngine. For the CPU I use the tensorflow lite interpreter....
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How to utilize dictionary data set for text classification?

I have a dataset similar to newsgroup20 for classification. With the training dataset, I have a dictionary data set that explains some jargons in the training dataset. These both are different data ...
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Building resume classifier based on keywords, what would be the steps & what are features and target in this case?

I went through this, as I have a similar requirement (at least what I think, correct me if wrong) of classifying resumes(.doc files) based on the profiles. I have a ...
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Is it possible to run sequential forward selection on a neural network?

I'm testing various models (Logistic regression, Random Forest, KNN, SVC, Neural Network) for a binary classification problem. So far I used both Sequential Forward Selection and Sequential ...
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Inferring latent variable distribution from binary data

I want to create a model to infer the behavior of a latent variable. As an example, let's assume the latent variable represents the level of extro/introversion of a person. The level of extro/...
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How do I find the distance between the truck and the lane?

I have a bunch of images from different trucks passing the road. The truck needs to be at a certain distance from the lane. Some of the trucks are way close to the lane (that you can see on the ...
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String indices must be integers

I was trying to encode the string values of the feature 'ProductCategory' into integer values but I got this error. Kindly help. And I would also like to ask if label-encoding this feature would not ...
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Keras input for multivariate classification with LSTM using current features and previous timesteps features and y values

I am working on a multivariate binary classification problem. What I want to do is to predict a binary classification given the features at the current timestep and the data (features+real ...
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How can solve data imbalance issue in MATLAB for a PatternNet?

I have built a Pattern recognition NN in MATLAB. I have two datasets, one for training and one for testing each of 4500 samples. The number of classes is 3. Out of the 3 classes, class #1 has approx ...
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If the entire production dataset is known is advance, should I use it when fitting normalization parameters?

I found in multiple sources the recommendation not to fit the normalization parameters on the combined train/test dataset when evaluating the model, to prevent data leakage. I presume this ...
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Is it normal for F1 scores to be lower on a binary classification task as compared to a 3-class classification task?

I am trying to understand if the F1 scores are higher for a binary classification problem than for a multiclass classification problem.
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Neural Network returning training data ratio instead of probability

I am trying to create a neural network from scratch using numpy. I have created a network that can classify iris data base to a high degree of accuracy. I am facing the problem that sometimes ...
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Are there any algorithms for a classification problem involving unlimited classes, and only a few instances per class

The Scenario: A group of people must summarize specific parts of speeches they hear. They hear a new speech every day, and it's possible that multiple members of group are listening to the same speech....
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Deep Learning - Predict the relative order of data

I am facing a problem in which i want to predict the order of data. I was searching for research papers, however i do not know how this problem is named in academia. I encountered the following well ...
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Handling collection of featurevectors for classification

I have a data set where devices are represented by a collection of variables. These variables consist of several properties like a name, datatype, driver, limit values, etc. (mixed data; quantitative ...
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bias variance decomposition for classification problem [on hold]

I can see more mathematical relationship between MSE, bias and variance. But how to do that(mathematical intuition of bias variance) for classification problem.?
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How to get weightage of each factor for a prediction in a neural network classifier?

I am working on a model to predict which employee is going to resign from a firm. The dataset has columns like Date of Birth, Date of Joining, Department, Gender, Marital Status, Years at company etc. ...
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Best OCR approach on documents with different formats to find one specific information

Unfortunately, because of confidential data, I can't give a more specific explanation. The Problem So I've got a few documents that in general contain the same information but have different formats....
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Differences between class_weight and scale_pos weight in LightGBM

I have a very imbalanced dataset with the ratio of the positive samples to the negative samples being 1:496. The scoring metric is the f1 score and my desired model is LightGBM. I am using the sklearn ...
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How to choose our data set wisely?

I have a couple of questions and I was wondering if you could answer them. I have a bunch of images of the cars (side view only). I would like to train a model with those images. My objects of ...
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Confusion regarding the Working mechanism of Activation function

For binary classification irrespective of the model used, the sigmoid function is a good choice for output layer because the actual output value ‘Y’ is either 0 or 1 so it makes sense for predicted ...
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Feature vector of linear model

I read this paper that applies logistic regression to a dataset generated from a simulation they created. The dataset contains a set of binary vectors (called challenges) that looks like this: ...
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Should I back-calculate soft labels (probabilities) of my training set when I use probabilistic classifiers?

I have 2 datasets (D1, D2) to train 2 models (M1, M2). M1 is a probabilistic classifier, which outputs soft labels (probabilities of a sample belonging to each class) for a binary classification ...
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Feedback on duplicate and near-duplicate image detection

Good morning all, I recently completed building a script that does the following: Stores a list of all .jpg images existing in specified drive. Cleans/ids duplicates through md5sum Iterates ...
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How to predict based on multiple samples?

I am relatively new to ML so I apologies in advance if my question shows lack of understating of the field. The problem A particular study course has a high drop-out rate and we want to reduce it. ...
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Deep Learning with Keras. Classification problem with large data

I have looked on the internet and found a lot of discussion about image classification problems, but almost none of just classification problems without images. I am trying to build a model with Keras ...
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Ignoring unlabeled data for a single class

I have a data set of transactions with a binary flag labeling each as fraud or not fraud. However, it can take up to 90 days for a transaction to reveal itself as fraudulent. Sometimes it happens in a ...
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Neural net classifier outputting extreme probabilities

I am training a multi-label neural network text classifier (i.e. a given sample can have more than one label; most samples have exactly 1 label though): Single-layer BiLSTM producing a sequence of (...
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Reproduce Linear Regression Classification Masking Graph of ESL

I would like to reproduce the following graph from the Elements of Statistical Learning Chapter 4 Linear Methods for Classification. It shows the classification masking problem if using linear ...
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26 views

Why am a getting wrong prediction when combining two list of samples, which individually gives correct prediction?

So I am coding in Python. I have to set of samples. Set1 contains samples of class A and the other set, Set2 contains samples of class B. These samples taken are a part of the training dataset. When I ...
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How can I evaluate out-of-domain question in a domain-specific Q&A bot when I only have in-domain data?

I learned that some popular bots like RASA or LUIS will have "confidence scores" to evaluate the out-of-domain questions, but none of them provide documentation of how they calculate these scores. ...
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1answer
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Cat Dog classifier in tensorflow, fundamental problem!

I am trying to build an image classifier for a set of images containing cats and dogs. I am very new to the dark art of creating Neural Network models. I have had success building models with Keras in ...
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Is the activation function the only difference between logistic regression and perceptron?

As far as I know, logistic regression can be denoted as: $$ f(x) = \sigma(w \cdot x + b) $$ A perceptron can be denoted as: $$ f(x) = \operatorname{sign} (w \cdot x + b) $$ It seems that the only ...
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Incorrect Text Classification, But Accurate Model. Do I Perform Manual Text Classification For A Data Set?

I'm currently using Google's BERT pre-trained sentiment analysis model that is trained on an IMDb pos/neg review dataset. I'm using this model to predict whether tweets are positive (bullish) or ...
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What makes binary cross entropy a better choice for binary classification than other loss functions?

I'm reading this post where I came across this quote "Cross-entropy is the default loss function to use for binary classification problems." But what about it makes it the default and presumably best ...
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How to interpret a random variable in the variable importance?

I have a problem, for simplicity let's say it is a binary classification problem. I am trying to solve this problem using XGBoost. A standard output plot for any ML algorithm, is the feature ...
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Is “two-feature classification” appropriate and clear to describe this figure?

it seems that this figure can be used to elaborates the perceptron model and SVM model: Is it appropriate and clear to call this figure "two-feature classification"? Is this a canonical name?
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What is the geometrical representation of the y value in a 2-variable perceptron plot?

This figure represents a perceptron model with a 2 dimensional feature vector input. The hypothesis space of the perceptron is defined by this set: $\{y | y = w\cdot x + b\}$ What is the ...
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Keras Model always predicts the same class

I am currently trying to build a CNN classifier which takes a ector representing the log of an ECG spectrogram together with its class. What I am currently experiencing is the fact the model always ...
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non-separable assignments of the vertices of a hypercube

I have a question regarding exercise 14.17 in An Introduction to Information Retrieval by Manning et al. The problem is: "Assuming two classes, show that the percentage of non-separable ...
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How to Determine Specific Activation Function from keras' .summary()

I'm following a tutorial where a particular model is provided in .h5 format. Of course, I can call model.summary() on this model after loading it with ...
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25 views

How to prevent model from recognizing false Classes

Let's say that I have a model that can recognize Cats and Dogs. However, when I use a picture of a Cup or Human it generates a random prediction at 0.70 confidence. Should I use sigmoid instead of ...
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Do I use class weights to penalize false negatives or threshold optimization to improve recall?

I built a Random Forest model for a binary classification problem.Both the classes in the target variable are balanced. My main class of interest is 'class 1'. False negatives are more costly to me, ...
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138 views

ValueError: Found input variables with inconsistent numbers of samples [43,19]

So, I've been trying to split my dataset into a 70-30 ratio using train_test_split in order to work things out with sklearn's ...
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1answer
27 views

What is the intuition behind using LSTM for classification tasks?

LSTM is good for sequence prediction, because it can remember the previous context. What is the rationale behind using it in classification tasks ? In particular, they have used it for the following ...
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33 views

No correlation found between dataset features

I'm trying to build a classification model that predicts the price of New York taxi trips (year 2018). Datasource page Since the original file is very large (112 234 626 rows), I constructed the ...
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What could make a set of the train data more predictive than the whole train data

I took a sample of my training data and balanced it and then trained my model. The results obtained are more accurate than using the whole set of train data (balanced or imbalanced). My question is: ...
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Large no of categorical variables with large no of categories

I'm working on a binary classification problem where the dataset is slightly imbalanced (30% class 0 | 70% class 1). Most of my features are categorical with large number of categories. For example: ...