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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11 views

Difference between class_weight and loss_weights in Keras

Keras has parameters class_weight used in fit() function and loss_weights used in ...
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16 views

Why does a class weight fraction improve precision compared to under-sampling approach where precision drops?

I have an imbalanced data where the ratio between positive to negative samples is 1:3 (positive samples are 3 times higher than negative). For my case it is is important to have a higher precision (...
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52 views

Tensorflow model works for classification but not for regression (all predictions equal the output layer bias)

I'm trying to build a model for FX prediction. It's giving some promising results for classifying each period as buy/sell/neutral. When used as a classifier, actual returns are converted to 0, 1, or ...
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How to Predict Employee count of businesses using Keras classifiers

I am trying to predict the amount of employees a business has based on a set of input variables. I am using things like the business's age, transaction details, geographic location, business structure ...
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Derivation of Bayes classifier in Murphy's book

I am reading Kevin Murphy's Machine Learning book (MLAPP, 1st printing) and want to know how he got the expression for the Bayes classifier using minimization of the posterior expected loss. He wrote ...
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29 views

Deep learning model gives random results

First I am new to machine learning if it is an obvious question, I am sorry. ...
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User actions sequence classification

I have a training set where each row is a series of user actions on a website (logged in, sent an invoice, etc.) and times deltas in ms between these actions. Each row has a label — a corresponding ...
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32 views

An interesting task on machine learning [migrated]

There are 5 programs. Each program is a binary classifier, which classifies letters - "Spam" and "Not spam." All classifiers are independent and have an accuracy of 0.6. Suppose that there is a new ...
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Include date features in binary classification? [closed]

In binary classification and with features above 150, do you recommend dropping 3-5 date valued features?
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Multi-class classification configuration

1) What are the appropriate activation and loss functions for multi-class classification problem? Is it so that: Up to 2 classes $\rightarrow$ Binary classification $\rightarrow$ Activation: Sigmoid ...
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3answers
32 views

group the similar words

array(['Ruby on Rails', 'Ruby', 'AWS DynamoDB', 'Python', 'MySQL', 'Swift', 'Android', 'iOS', 'JavaScript', 'React Native', 'ReactJS', 'TypeScript', 'Vue.js', 'Webpack', 'Amazon Web ...
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1answer
85 views

How to interpret classification report of scikit-learn?

As you can see, it is about a binary classification with linearSVC. The class 1 has a higher precision than class 0 (+7%), but class 0 has a higher recall than class 1 (+11%). How would you interpret ...
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Model confusing classes

I'm training a bidirectional lstm with attention on a dataset with text data and six target classes. The F1 score on the test set by class is about 0.7 for four of the classes, and about 0.35 for ...
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3answers
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NLP and one-class classifier building

I have a big dataset containing almost 0.5 billions of tweets. I'm doing some research about how firms are engaged in activism and so far, I have labelled tweets which can be clustered in an activism ...
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How to use “related” and “unrelated” as classes rather than multiple classes?

I have a dataset with about 15 feature columns and about 1000 rows that I'd like to use for supervised training. Every row can be classified as "related" or "unrelated" to another row. About fifteen ...
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1answer
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Can a recommendation system be used as a binary classifier?

I have a computer-generated music project, and I'd like to classify short passages of music as "good" or "bad" via machine learning. I won't have a large training set. I'll start by generating 500 ...
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How to estimate the marginal distribution of a class with respect to one predictor in a classification task?

I have a dataset with a binary dependent variable $y \in \{0,1\}$ and a set of predictors $x1,x2,..,t$. Here, $t$ is the time in minutes (in 24 hrs, that is $t \in (0,1440)$). I want to estimate the ...
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1answer
33 views

Problem with sort by and group by in pandas

I have a DataFrame with duplicate id's but have different dates. For Example: ...
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20 views

Data transformations in hierarchical classification

I am building a hierarchical text classifier using the Local Classifier Per Parent Node (LCPN) approach with the 'siblings' policy as described in the PDF: E.g. if we have the classes 1.1, 1.2, 2.1, ...
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Why crossvalind and cvpartition results are different?

I did a Test on my data set with "cvpartition" and "crossvalind" functions (in MATLAB) with the same parameters and data set, but why the error results are different and which one is correct? Codes ...
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1answer
63 views

Why might trees work so much better than boosting classifiers?

I am predicting 10 classes label encoded using scikit-learn with 6 factors, 1.2M cases. DecisionTreeClassifier RandomForestClassifier ExtraTreesClassifier give accuracies (and precision and recall) of ...
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15 views

Balance two crossentropy losses with different number of neurons

I have a model with a few outputs, each output with shape: Shape: (batch_size, labels_1) -> softmax -> ...
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1answer
30 views

Predict_proba() probabilities distribution [closed]

I’m trying to calculate probability of class 1. I’m using gradients boosting (catboost classifier) Is it normal to have an equal rate of positive classes in every predict_proba() bucket? e.g.: [...
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1answer
32 views

Is there a common strategy to measure if a difference-significance of two areas under two ROC curves

I conduct sound detection experiments with mice. I have a stimulus sound and a "noise" sound that shoukd be ignored. I want to measure how well the mouse ignors the noise (with respect to, say, ...
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1answer
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Improve performances of a convolutional neural network

I am doing image classificaition, and to do this I have built the following neural network: ...
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16 views

Association, classification and decision rules - terminology?

Association rules as well as classification rules, both need to have a conjunction of values of the input attribute in their precondition. In the conclusion the association rules can have arbitrary ...
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28 views

Conv Net Model is overfitting

So I made a convolution neural network to classify between different phonemes. My input datasets are a series of 0.4-second long spectrograms, the labels are each an individual phoneme that happens at ...
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1answer
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Naive Bayes implementation: why Laplace smoothing is different from theory?

Let's have a Naive Bayes Bernoulli classifier with $n_C$ classes and $n_F$ features. According to the formula in here and here and almost every theory book I could see, Laplacian smoothing means that ...
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Fragment level classification

Is there a tutorial or an example on fragment level classification task? I have to identify and classify specific n-grams in a text? The training data contains examples labeled as span or not span. (...
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2answers
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why an advanced LSTM model produce the same results as a simpler one?

I have implemented the model proposed in this article which is a text classification model that uses sentence representation rather than only word representation to classify texts. ...
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4answers
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Image Classification using Single Class Dataset using Transfer Learning [closed]

I only have around 1000 images of vehicle. I need to train a model that can identify if the image is vehicle or not-vehicle. I do not have a dataset for not-vehicle, as it could be anything besides ...
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1answer
26 views

How much is the Class Imbalance Problem rates?

I'm working on a data set and wanted to know is there a standard rate about Class Imbalance problem or not? I have 47 samples in Class A and 150 Sample in class B , should I use Class Imbalance ...
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4answers
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scaling images for image classification

I am trying to do image classificaition with a dataset that contains images of different sizes. The images are in a folder called Train, which contains 4 subfolders callsed HAZE,RAINY,SNOWY and SUNNY. ...
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2answers
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Can I use more features for my training data than my test data will supply?

I am pretty new to the data science game so pardon me, if the answer to my question should be a no-brainer. We are looking at manufacturing / quality data where products are labeled 'okay' or 'not ...
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1answer
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Error: An operation has `None` for gradient with categorical_crossentropy

I am trying to train my discriminator network using Keras with TensorFlow backend. The network is meant to classify the input into one of the 9 output labels. I am passing a 2D input (height, width, ...
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2answers
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Classification accuracy based on top 3 most likely classifications

My goal is to recommend jobs to job seekers based on their skill set. Currently I'm using an SVM for this, which is outputting one prediction, e.g. "software engineer at Microsoft". However, consider ...
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1answer
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Lime Explainer: ValueError: training data did not have the following fields

I'm attempting to gather ID level drivers from my XGBoost classification model using LIME and I'm running into some odd errors. I'm using this link as a reference. Here is the overall code that I'm ...
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1answer
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Classification of images of different size

I am doing image classification using Convolutional neural networks, but I have a problem, because the images I want to classify are all of different sizes. My code is the following: ...
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2answers
97 views

model with features of different sizes

I want to train a model (either classification or regression, doesn't matter) with features/inputs of different sizes, but I am not sure how to do it. For example, for each data-point, feature 1 and ...
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1answer
52 views

Random Forest Overfitting, issues with mtry=1?

I am constructing what is known as an 'Expected Goals' model for football. This metric measures shot quality and a probability is assigned to a shot to achieve this, i.e. the chance a shot will be ...
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How to change classification model architecture for a new target application

I'm new to Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple architecture for my own ...
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Is using cross-entropy enough to ensure the output is a distribution probability?

I am following along https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html. In this code, the last layers of the pretrained networks are linear. The loss used in this ...
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1answer
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Transfer learning between Language Model and classification

Following this fast.ai lecture, I am trying to understand the mechanism of Transfer Learning in NLP from a general Language Model (LM) to a classification problem. What is exactly taken from the ...
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25 views

What is the effect of changing the seed value on the classification results?

I used weka program to make a classification, first I used a dataset using the explorer and the seed value was equal to one, then I used the experimenter for the same dataset and the seed value was ...
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Is kFoldLoss simply the average classification error?

I'm using a kNN classifier in MATLAB to classify ECG signals, with 5 fold cross validation I get almost 97% accuracy. However, I'm not entirely sure if this is truly the accuracy value. By default the ...
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3answers
215 views

ROC curve interpretation

I trained a CNN model and a combined CNN-SVM model for classification. I wanted to compare their performance using ROC curve but I was confused which model is better. How to interpret the given ROC ...
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1answer
18 views

what does random seed value mean in weka?

I use weka to make a dataset classification but there is an option in classifier evaluation ( random seed for XVAL/% split). What does this option mean? ,and what is the seed value ? ,and What is the ...
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1answer
18 views

Attitude to text mining and preparing tokens, irrelevant words, low accuracy

For purpose of quite big project I am doing a text mining on some documents. My steps are quite common: All to lower case Tokenization Stop list and stop words Lemmatizaton Stemming Some other ...
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Capsule networks for binary classification not training brain images classification

Currently I am trying to implement a capsule network using Xifeng Guo's Keras code for capsule nets. I have a dataset of brain tumor images with 98 negatively labeled instances and 155 positively ...
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Classification Algorithms For Noisy Problems

Dear fellow data scientists I work in finance and have decent experience with neuronal networks. Right now I am facing a challenge where I need to classify a set of signals. The data set looks ...