Questions tagged [dataset]

A dataset is a collection of data, often in tabular or matrix form. This tag is NOT intended for data requests ("where can I find a dataset about ...") --> see OpenData

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24 views

I need a dialogue dataset [migrated]

Where can I find a dataset of 2 people chit-chat dialogues? I need the data to be of full conversations, from "Hi" to "bye" so to speak.
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List of naughty faces?

An Australian sporting league simulated live crowds using cardboard cut-outs to fill empty stadiums during COVID-19. Fans were allowed to submit their faces to be used on the cutouts, which resulted ...
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German Chatbot or conversational AI

I want to build a chatbot mostly BERT(Transformer) based in the German Language. But I do not find any German chatbot data set! So does it make sense to use google translator API to translate the ...
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Public benchmark datasets posted with expected/record scores for sanity check?

When I use a new modelling tool or approach, I like to do a quick sanity check on a public dataset to make sure I'm getting good (but not "so good it looks fishy") scores. There are several clean, ...
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Is there any relevance of normal distribution theory in data science? [closed]

Normal distribution theory is popular especially in statistics and psycometry. How come it has become relevant to so-called datascience
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Approaches For Recommender System Using Complicated Novel Dataset

I have a question about the best approach(s) I should take in building a recommender system for a project I'm working on. I have created a dataset. The dataset has the following: 400,000 users For ...
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What is difference between standard normal distribution and feature-scaling? [duplicate]

I am not sure whether standard normal distribution is helpful in feature scaling. The tag - feature-scaling seems to convey that it is one of the scaling method
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Where are some good online covid 19 genetic datasets? [closed]

I want to carry out some research with covid19 genetic datasets that include people infected by corona virus and people that aren't infected by it. Does anybody know any good ones? My main purpose is ...
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Is my bayes classification right or meaningful?

I have this dataset and I am learning about Bayes Classifier. After data cleaning, I have tried to use bayes classifier on it. I used R with this code: ...
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Apriori gives 0 rules

I am trying to use apriori() on this dataset. After cleaning it, I made all attributes categorical with as.factor(). Then I uset these instruction: ...
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How to draw a sample from data set with respect to a given categorical or numerical variable based on given freely chosen distribution? (Python)

Say I have a data set for some past period. Now new data appears and for a given variable in the data and we find that the distributions have shifted (for example with "age" it would be that suddenly ...
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Suggestion of dataset

I am implementing my own deep network, but I am not so good at calculus so my network only works for binary data in the moment. I have been searching for big tabular datasets that are for binary ...
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What makes a good image dataset to compare biological NNs to ANNs?

I'm going to be comparing biological NNs to ANNs based on compounded adversarial attacks, but wish to know what makes a good image dataset to test on biological NNs? Going for image classification. I'...
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Data-preprocessing for Machine Learning model

I am confused about how to preprocess range based category such as age, tumor-size & inv-nodes. Should I take an average of the limits, as in - 14.5, 24.5 and so on or do one hot encoding of the ...
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How to find a Employee Performance dataset

this question might be out of the context. but, I am doing my final research on Predicting Employee performance in IT sector (if not any other sector) So I have been thoroughly going through ...
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1answer
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Minimum number of samples on a CNN

Related to this paper, could it also be applied to convolutional neural networks? I ask this because FNN and CNN share many characteristics This is the formula: Where ...
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Comparing the two feature sets

I am working on a classification of two feature sets derived from a dataset. We first obtain two feature matrices derived from two feature extraction methods. Now, I need to compare them. However, the ...
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Is feature scaling correctly defined? [closed]

Tag on feature scaling says - Popular feature scaling types include scaling the data to have zero mean and unit variance, and scaling the data between a given minimum and maximum value. This tag ...
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Machine learning methods on 1 feature dataset

Assuming I have following dataset but much longer. Can I use any machine learning methods having only one feature? Giving Name and predicting Fullname. I'm newbie ...
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What's my target variable?

I am beginner in data science. I have this "aids" dataset from "mdhglm" package in R. dataset = aids, info = Repatead Measures on AIDS Data ...
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1answer
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How can I select data from a Tensorflow Dataset data collection?

Is there any way to select features or labels from a tensorflow Dataset without using numpy conversion methods or iterate through? The simplest example I found is: ...
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Same values for PCA Loadings results

I've recently performed a Principle component analysis for my masters thesis where I have 25 network datasets, formatted into graphs and applied 5 measurements to each graph. The measurements were ...
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Additional Explanation Required for KbinsDiscretizer

I am a newbie learning data pre-processing. I have few questions on encoding of categorical data. Q(1) Are ColumnTransformers compulsory to apply any of the various encoding methods on 2d data? Here'...
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Is there a way we can narrow down the best range describing a dataset (other than IQR and Min-max)?

I have a dataset of the prices of products for different categories. I want to get the best range which can describe the prices of that category using the Product Data. I have already applied IQR and ...
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Dataset + Feasible Applications for Multichannel Data

Would you please share with me the feasible application in real world related to the classification task for the multichannel data? (other than the data related to the brain applications).
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Metric/calculation to measure relative popularity/frequency of x by variable y

Apologies if this is not the right place for this question. I figured this has some data science / general analytical applications, not sure where else to ask. Please let me know if I should do ...
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Nice real data sets for testing DBSCAN?

I'm looking for real datasets on which I could test my DBSCAN algorithm implementation, that is, a dataset of points in (ideally 2 dimmensional) space, or a set of nodes and info about the distances ...
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I am not getting classification output by predict_generator()

I am trying to classify pre-downloaded images from my dataset to "Rock" , "Paper" , "Scissor" classifications but I am getting outputs as numbers. I have already divided the dataset to Train folder ...
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how to shuffle the data for model.fit with custom data generator?

So trainfiles is a list that contains the files' directory and name e.g. ['../train/1.npy' , '../train/2.npy'] and then I create a dataset as shown in the middle of the code then I apply it to model ...
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What is standard in Data Science for using Audio Features and Text Sentiment to predict affective annotations

I am trying to formulate a study on a dataset that I have gotten access to. I have done some Machine Learning projects but this one is getting a bit hard to comprehend as to what to do. I have the ...
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Brightness Adjustment During Pre-Processing and Model Accuracy

I have image datasets that consists of multiple level of brightness. Usually darker are more than the bright. All these images are collected from different places. Some of the images too dark that to ...
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1answer
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How to train-test split and cross validate in Surprise?

I wrote the following code below which works: ...
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1answer
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Logistic Regression: Is it viable to use data that is outdated?

TLDR: Want to predict who makes the playoffs (1,0), but there are more playoff spots now than there were in the past, is it okay to use that past data? I want to use binary logistic regression on MLB ...
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1answer
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What's an appropriate datastore for variable length sequence data for PyTorch consumption?

I have a large number of sequences - potentially hundreds of thousands - each consisting of between 100 and 10,000 items, which each consist of about 5 floats. I need a datastore that can rapidly ...
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EEG Dataset Concerning Neurophysological Disease

I had a lot of search to find an EEG dataset concerning Alzheimer's disease (or any other neurophysological disease), however, I could not find one. I am particularly interested in a dataset with ...
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Single numeric features row and multiple text rows corresponding to numeric data. How to classify in dataset?

For example, take a review of a product. I have numeric information corresponding to the product and also multiple reviews and I have to output a binary class for the product. How can I predict when I ...
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Data storage for Intrusion Detection System

I write a IDS(in C) for a KNX network for my thesis. For this I just store all the telegrams within a sqlite database. But I'm not sure if a sql database is the best here. I want to "ask questions ...
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Data mining: Clique based clustering to make comparison in social network analysis

I am a very beginner in data mining. I want to work on Clique based clustering method. I want to make a comparison between various datasets for social network analysis or community detection of social ...
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Methods of working with unbalanced dataset

I've got problem where I need to classify the images for about 400 classes and to do this I'm using model with neural network. In my dataset (about 300k images) there are classes represented by about ...
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1answer
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Table transformation using Numpy, Pandas

I want to transform a table from this : To This : Explanation: basically I'm trying to create a "Sankey chart" for that I need this type of format. So From Table 1(1st Image): Using Date and ...
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1answer
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Suitable sample data set to test machine learning algorithms

I'm new to Machine Learning and I just came across the sci-kit package. On this interesting page there are many toy data sets used to test different clustering algorithms. Each data set has a unique ...
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supervised learning : approximating a priority function

I am facing the following supervised learning problem: An object is fully characterized by its position in $R^n$. There are $m$ objects. There are fully observable (i.e. their positions are always ...
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How to identify corresponding record of a car from a semi-structured string?

I am trying to build an application that can take a record of a car from different websites, compare it to data i have in a CSV file and return me the matching row. Each website will present and ...
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How to find/select appropriate dataset for building an ERD with some complexity?

I have a course project that needs me to build a ERD over a dataset, which has relatively clear business background, but I finally find that there are not explicit entities (which are pivotal for ...
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What's the best small dataset to train a RNN?

I work on a neural network library in C++ and I'm in the process of implementing recurrent neural networks. I run my tests on a GitHub server on different datasets, Iris and Wine for simple unit tests,...
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Benchmark queries for Benchmark dataset with ranked list of documents

I aim to evaluate the ranking of an information-retrieval system. For a benchmark dataset like TREC, I have followed the qrels file which has list of documents for a particular topic (query) with ...
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23 views

Change format of table

How can I change the table format from this: To This?: Is there any way to do this in Python using pandas or NumPy?
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what is the difference between copying and storing a data set in an remote environment vs mounting the data there?

For image processing do we generally copy and store data to the remove server where we train our model or we mount the data ,as some sort of reference ? Is there any difference or are they same ?
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How to standardise/normalise csv data in a tensorflow 2 dataset

Does anyone know how to apply standardisation (or normalisation) on the numerical features of a dataset loaded in batch via tf.data.experimental.make_csv_dataset in ...

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