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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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Extending DTW 1-NN Classification to On-line Scenario

I am familiar with Dynamic Time Warping classification using a 1-nearest neighbour approach. However, in most benchmark datasets and applications, it used ex-post, i.e. classifying a time series after ...
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Evaluating regression model in python - How do I interpret my results?

I'm trying to predict some 'malicious score' using RandomForestRegressor, and i'm trying to evaluate my model performence. I've tried all of scikit-learn documentation functions to evaluate, but not ...
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Bounding Boxes in YOLO Model

The YOLO model splits the image into smaller boxes and each box is responsible for predicting 5 bounding boxes. My question is how does the model make these bounding boxes for every grid cell ? Does ...
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Description matching between two columns

I have a DataFrame with two columns, let's call them column A and column B. Each column is identified with a unique ID and a description. Usually, each idA is in a 1-1 relation with idB. ...
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Binary Classification without machine learning tools

I have to write a binary classifier for my company that should be as simple as possible and doesn't use machine learning libraries (and I also should not code too sophisticated algorithms by myself). ...
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Which sklearn classification would perform best on shape= (2000, 1024) w/ binary features?

I have a training data set that is roughly 2000 rows by 1024 columns all binary data either 1's or 0's. The labels are numbers that equate to the letters of the alphabet so this basically a hand ...
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Intuition xgboost weights and log-loss / final leaf scores

Can somebody help clarify some points: Firstly; Consider a tree at the $ith$ iteration for a binary classification. Each tree assigns a log-loss score to each of the terminal leaf nodes which can ...
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Deep Learning ROC and Average Precision Curve Results

I used Vgg16 to create a deep learning model and the dataset is imbalanced so, I used class_weight argument in fit_generator method. The model result as the following: accuracy= 98.9% and loss= 0....
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Estimating prevalence in a population as a credible interval after predicting labels with a binary classifier

I'm looking to get an estimate of the prevalence of 1's (i.e. the rate of positive labels) in a very large dataset that I have. However, I am hoping to report this percentage as a 95% credible ...
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Any practical improvements worth trying over plain LSTM in text classification?

I have a dataset of about 1 million tweets corresponding to about 30,000 user accounts, labelled with binary data (classifying the tweet as written by a bot). With that amount of data, I could use a ...
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Multiclass classification based on a single continous variable

I have a large list of alarms, collected from an automated manufacturing cell (categorical). Each of these alarms has an associated duration time (continuous variable), describing how many seconds it ...
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When creating a classification model, should predictors with little correlation to the response variable be included in the model?

I am building a predictive model designed to predict attrition within my organization. I am trying to decide whether to add certain predictors to my model. I used a Kruskal-Wallis rank sum test to ...
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Dataset Creation for Images

I am creating an image dataset of objects. We have 15 classes of objects and need to provide a color to the objects also. What ...
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Is my model over-fitting (LSTM,GRU)

I have small corpus max 150 text utterances, which is again distributed among 5 categories. To test I started with basic deep learning model, where i used word2vec embedding, added 1D convolution ...
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Is there a consensus on which voting to use in VotingClassifier and why? Hard voting vs. Soft voting?

I get much better accuracy in soft voting (e.g. 0.5) vs hard voting (e.g. 0.8). Should i report both? or can i depend on one of them? Am i conservative if i chose hard voting? I do understand the ...
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How can I classify these aerial images?

I want to use R to classify high res aerial images (4 band tiffs). The images are of residential food gardens in Portland. I want to train a model to be able to identify if there is a food garden ...
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Why does the votingClassifier in sklearn.ensemble gives higher accuracy than each of the classifiers that make it? and should i depend on it?

I am running an ML classifier on my data. I used SVM, RF and KNN. I used GScv for each of them and then used votingclassifier.The accuracy i got in each classifier independently was low, but from the ...
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With a continuous target variable and a pre-defined cutoff, should I do classification or regression?

In my machine learning project, the target variable is continuous. Also, we have a pre-defined cutoff, which can separate the target variable into two classes (e.g. High and low). There are two ...
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How to detect influence on behavior

From a behavioral study data was extracted. The study was about how people change their eating behavior, following visual cues. There were to groups of people: One was shown visual cues and then it ...
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Using machine learning to classify pages on website based on HTML structure

I'm currently working on an audit of a site for a client. One of the problems we've run is that all the articles are in a CMS; but depending on the author, were authored with different methodology. ...
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Support Vector Machines VS LSTMs: How well it is justifiable to use LSTM for its Generalization properties?

The question is pretty straightforward, How well one can justify using LSTMs(Neural Networks) for text classification task in terms of "Generalization" compared to classic support vector machines(SVM) ...
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How can I detect significant changes in my data?

I have a dataset like this: ...
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How to interpret F2 metric based on test set?

I have trained a neural network to detect positive classes in unbalanced data, in my set there are around 1-5% of positive classes. To evaluate my model I have used F2 to ponderate both recall and ...
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Do C 4.5 or C 5.0 perform multi way split or binary split?

Suppose that I am using a continuous variable as an independent variable (although a bad choice) for C 4.5 or C 5.0 (tree based classifier). I am having a hard time figuring out does C 4.5 or C 5.0 ...
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Data model and algorithm for recommending “related” interests

On my app, when a user selects an interest (example: ios), I'd like to show related interests (swift, xcode, apple, etc). I have a list of around 700 interests/tags (about 300 of them can be ...
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Using linear chain conditional random fields for sequence classification

Can linear chain conditional random fields be used for classification (such as a binary classification problem), rather than POS tagging? I have been working with the keras-contrib package but ...
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Document Separation & Classification

I receive Searchable PDF files that comprise of scanned pages from multiple documents (structured documents such as forms and unstructured documents such as letters). As the files do not contain a ...
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How to visualize Ensemble Models ( Random Forest) with 1000 estimators

I am working on classification problem where I need to categorize the user in buy/ non-buy category. I have around 100 + features or predictors to predict the behavior of user. I tried to implement ...
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Keras : efficiently create a sample to perform ZCA whitening

I am using Keras' ImageDataGenerator class to generate training & validation dataset for my network. As far as I understand, when one wants to use ZCA whitening, one has to first fit the data ...
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Best way to build a wave classification system

I want to make a classifier for waves such as following: Above image is from: http://www.invisiblesbook.com/equal-temperament-tuning/ I believe, I will have to extract features from raw input using ...
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1answer
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Classifying objects based of a varying number of the same type of feature vector for each object

For a congressional session, I have created a doc2vec model of speeches made. Using the vectors from this model, I have a dataset of each congressperson, their political affiliation, and a list of the ...
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Keras : get labels back from saved 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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Classification of Conversations in Text

I am trying to pick a technique for classifying conversational text. I am concerned about treating the problem at a level of fidelity of each individual message because people often say things like, "...
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Intiative detection problem

I currently try to wrap my head around a problem of detecting an initiative in a company report document. The following are the types of initiatives a company can report: health, no_poverty, ...
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What kind of algorithm should I use to build ML model that can predict just next reoccurence of an event in the future (at irregular time interval)?

I'm quite new to machine learning and statistics. I've a dataset from some ecommerce sale's history. It's almost 2k instances, and features include personId (string), productCategory (string/...
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How to visualize results/errors of multilabel classifiers?

For multiclass classification you would normally choose a confusion matrix to plot the error of predicted classes against the target classes. What is the best way to visualize errors of multilabel ...
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Naive Bayes classifier - dealing with empty strings

I was wondering if you can help me with something. I am building a Naive Bayes classifier for a project and while testing it I noticed that it marks empty strings for positive. When i checked the ...
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Conditional Probabilities on store data

I have data on store level purchases, Panel-level purchases and demographic information of loyalty cards. In the store purchases information, the data consists of a product code which can be assigned ...
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Working with many unique values in a column

I have only learnt basics of data science about 4 months ago. And now I am working on project. This is my code: https://pastebin.com/er1EA7pZ This is my data: https://www.kaggle.com/grosvenpaul/...
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1answer
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Linear Discriminant Analysis + bayesian theorem = LDA classifier??

I am new to machine learning and as I learn about Linear Discriminant Analysis, I can't see how it is used as a classifier. I can understand the difference between LDA and PCA and I can see how LDA ...
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2answers
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Neural network for Multiple integer output

I have a data set that contains 135 input features and 132 output values to be predicted. The input features are all numeric floating point values and each output value would be an integer between [0,...
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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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What do neural networks learn first?

I'm running some experiments with NNs (actually I'm running an LSTM classifier), and I stumbled across a question I haven't found the answer so far. What do NNs learn first? When we train a network ...
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2answers
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Create a binary-classification dataset (python: sklearn.datasets.make_classification)

I would like to create a dataset, however I need a little help. The dataset is completely fictional - everything is something I just made up. Since the dataset is for a school project, it should be ...
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Cross entropy loss increase but precision get better

i am working on classification model. my test result shows precision is getting better despite loss is increase. is it just the nature of my data or is there some kind of theoretical explanation?
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Softmax probabilities for SVM

I have a simple binary classifier using Alexnet where it outputs if an apple is class 1 or class 2. Currently, I have the code as below ...
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Unable to converge in my multi layer neural network while training on MNIST

I have been trying to implement neural network from scratch using numpy library only.... I have checked thoroughly and the net is able to converge in very simple dataset( 2d graph ) but I wanted to ...
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Data Cleaning for Discrete Features. Data list that contains null or N/A data

I ran into this kind of problem in my projects and I want to see if there more ways to solve it. EXAMPLE There is some data about apples and pears and the features are dominant color (red, green) and ...
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Activity recognition with binary sensors

I have a bunch of streams coming from a set of 28 binary sensors around a SmartHome like this: Where: OBJECT: indicates the name of a binary sensor STATE: is obviously the state of the sensor at ...