Questions tagged [preprocessing]

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15 views

Group data without losing information

Context Imagine that I have a dataset about sending messages. Each row as user_id, a batch_id, a ...
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1answer
429 views

Using pandas get_dummies() on real world unseen data

I made a ML model, trained and tested it with my data containing categorical variables. To create dummy variables I used pd.get_dummies() before the split. I now ...
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1answer
74 views

what is correct way to perform normalization on data in Auto encoder?

working on anomaly detection problem. i'm using auto-encoder to denoise given input. I trained network with normal data(anomaly free). so model predict normal state of given input. Normalization of ...
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45 views

Dummy variables for unseen data in R

I got the following problem: When I trained my model I created my dummy variables(before train-test split) in the following way: ...
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0answers
124 views

Decision Tree - Preprocessing for very sparse features

How do we pre-process data for very sparse features for a decision tree? From this Turi documentation for decision trees It mentioned this: Why chose decision trees? Different kinds of models ...
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1answer
36 views

How to deal with name strings in large data sets for ML?

My data set contains multiple columns with first name, last name, etc. I want to use a classifier model such as Isolation Forest later. Some word embedding techniques were used for longer text ...
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1answer
351 views

Why does not log transformation make the data normalized?

Having some skewed features as shown in the following figure. I am trying to imply log transformation to the feature called vBMD(mgHA/cm3). I run the following ...
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1answer
236 views

Mutate with dynamic column names dplyr

Hi I have this dataset (It has many more columns) ...
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1answer
35 views

How to discretize certain features with a feature set?

I am working with typing data with timing features(unit: ms) and some of the features are based on the keyboard keyCodes(positive integers, range:[8, 222]). Currently, I use ...
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0answers
59 views

Image preprocessing: How to resize / align / cut images of various sizes?

I want to create a new dataset for image recognition. If I have Object A that I want to recognize in images, and multiple images of various different sizes, how do I preprocess them so that they ...
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118 views

Should I remove the trend from timeseries when using DeepAR

I saw that for some other algorithms for timeseries data it is advised to remove trend and seasonality before doing the prediction (ex: ARIMA and LSTM) I figured out from the paper that SageMaker's ...
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2answers
2k views

Loading own train data and labels in dataloader using pytorch?

I have x_data and labels separately. How can I combine and load them in the model using torch.utils.data.DataLoader? I have a dataset that I created and the ...
2
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2answers
36 views

How to Normalise features for small datasets?

I am working with a small dataset ( N = 50 ). I would like to normalise my input features. I am facing the following issues: Because of the small size of the dataset the range of training input ...
2
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1answer
66 views

Clustering time series based on monotonic similarity

Context I am involved in a task of clustering 1500 time series of 500 observations into a few number of clusters. The time series share all the same observed property at different spatial locations, ...
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0answers
31 views

Construction Adjacency matrix for GNN

A bit of a novice question, my data comes in the form of 2D hit points, my goal is to perform node/edge classification to find out whether this graph is my signal or background. My question is, when ...
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2answers
129 views

How to extract and classify data from a column in excel?

I have a column in an Excel sheet that contains a lot of data separated by || delimiters. The data can be classified to some classes like Entity, IFSC codes, ...
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0answers
22 views

Calculating unaffected data [closed]

Some data sets values are missing. Missing values are spread along 1.5 standard deviation from the median with distribution mean = 0 & variance = 5. How much data would remain unaffected in %. Why?...
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30 views

Checking skewness of variables

I follow a tutorial for the current dataset I'm working on. In this tutorial the target variable is check for skewness, and corrected het for by by taking the log transformation. Hereafter, skewness ...
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2answers
52 views

Pre-processing on MRI images

I have MRI images of brain tumors collected from a hospital (not a benchmark dataset). And I am planning to use them to predict/classify tumour types using a typical machine learning approach: texture ...
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1answer
107 views

LSTM for prediction of next location step - help with standardization

I have a few questions regarding the topic and I hope someone might have experience with any of them. What I am trying to do is train an LSTM network, whose input is a sequence of N steps in a XYZ ...
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0answers
20 views

Specific data formatting techniques for discontiguous time series?

I'm facing a predicting problem for food alerts. The goal is to predict the variables of the most probable alert in the next x days (also any information I could get about future alerts is really ...
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1answer
25 views

Loading Data into DW: Direct Insert from PreProcessing vs PreProcess and then loading from CSV files

I have a preprocessing script (google cloud function) that generates files (stored in Google Drive). I want to load those files in my DW (Big Query). What are the pros and cons of: 1) Running the ...
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1answer
87 views

Encoding multiple observations from the same feature space

My data contains multiple observations of categorical feature.The feature space is medical symptoms, so the data for this feature is like : ['fever','pain','yellow skin' .... ] .The amount of symptoms ...
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1answer
23 views

Image normalisation methods

I have found some research papers specifying explicitly the normalisation technique they used to get the results. What difference do IMG /255.0 And ...
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0answers
86 views

Remove attributes with missing values exceeding a given threshold in WEKA

I imported csv file into WEKA, i have features that have missing value that has missing value percentage of 70% or above, i want to remove these features by weka or also sort that features by missing ...
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1answer
179 views

Cleaning data automatically [closed]

Do you use automatic cleaning tools for data? I mean something similar to h2o.ai's auto ml function but applied to preprocessing data. Or do you always clean data 'by hand'.
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2answers
103 views

data pre-processing before image classification

I'm working on a machine learning project, Images classification (shape: 100 x 100)-> (vector of 10000), I did some pre-processing before applying decision trees algorithm , I got an accuracy of 55 % ...
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0answers
526 views

Columntransformer multiple columns with vector inputs

This is perhaps more of a coding question than data science so apologies if this is not the right platform to ask this. My question is related to the sklearn's <...
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1answer
55 views

What is the the cost of combining categorical variables?

I have 2 categorical variables e.g. state and city. Missing are only in city. As opposed to throwing out all observations with missing values for city or throwing out city all together I was ...
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1answer
42 views

Does discretization of continuous features also lose information about distance?

During discretization, it "squashes" nearby values into one bin, losing a little bit of information along the way. But doesn't it also lose information about distances of features? For example, if we ...
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2answers
90 views

Transformation of categorical variables (binary vs numerical)

When using categorical encoding, I see some authors use arbitrary numerical transformation while others use binary transformation. For example, if I have a feature vector with values A, B and c. The ...
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1answer
42 views

Is it correct to use non-target values of test set to engineer new features for train set?

Suppose, I have a dataset with a feature_1 value and a target value. Now, I want to engineer a new feature by creating relative value by subtracting mean from each value. Question: Can I (1) use ...
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1answer
179 views

LSTM - How to prepare train from a dataset which contains multiple observations for different events

I m using LSTM in a project related to MobiFall dataset which contains falls and daily activitives - such as walking, sitting etc - sensed by accelerometer, gyroscope and orientation sensors in x,y,z ...
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0answers
69 views

How to deal with attributes that can vary arbitrarily for each sample?

Let's say we are trying to classify cars into five different categories. For this, we have a lot of samples described by color, brand, model, year of manufacture and so on. For instance, imagine ...
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0answers
136 views

Audio signal signal processing for background noise reduction or removal

I am performing simple audio recognition using tensor-flow to spot key word or hot word detection. The graph takes the microphone input directly and performs "Audio spectrometer --> mfcc's --> and ...
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1answer
407 views

pandas: How to impute the categorical column by the nearest neighbors?

I've a categorical column with values such as right('r'), left('l') and straight('s'). I expect these to have a continuum periods in the data and want to impute nans with the most plausible value in ...
1
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2answers
63 views

Is there any tool for data visualization and manipulation?

I have a time series data set that I need to manually label them for supervised learning. What I am doing now is using excel to plot, and when I see the pattern that I want, I hover over the data on ...
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1answer
45 views

Missing Values in Classification

I'm working on a classification problem. I'm trying to build a model which can predict if a bank client will get a loan or not. Some of clients have co-borrower and the majority don't. I also have ...
6
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1answer
2k views

Difference between OrdinalEncoder and LabelEncoder

I was going through the official documentation of scikit-learn learn after going through a book on ML and came across the following thing: In the Documentation it is given about ...
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2answers
85 views

Can preprocessing the whole population cause data leakage?

Introduction I understand the problem of data leakage that could be caused by the preprocessing step when our training and test sets are just samples of an unknown population. The preprocessing ...
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0answers
45 views

Any tool that can help on manually label a time series data please?

i am working with a 10 years weekly financial time series data set, which has the standard format date open high low close volume. i would like to manually label (classify) the data set with label/...
2
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1answer
123 views

A single column has many values per row, separated by a comma. How to create an individual column for each of these?

As you can see below, I have a column called code with multiple values per row, separated by a comma. How can I create a column for each of these codes and make ...
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0answers
54 views

How standardizing and/or log transformation affect prediction result in machine learning models

I recently ran an elastic net model on my data. My predictors are mostly skewed. I found my model perform slightly better when I standardize on log-transformed data than standardizing on original data....
1
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0answers
134 views

Lowercase texts before tokenizing as pre-processing step for alignment

I am pre-processing some texts and I wonder what the best practice is when preparing your texts for word alignment. I don't know how aligners such as fast align and GIZA++ work under the hood, but I ...
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0answers
62 views

Transposing a dataframe (time-series)

I'm working on event-forecasting problem for a supermarket, and the data frame I have looks like (sorry for formatting): ...
15
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2answers
7k views

StandardScaler before and after splitting data

When I was reading about using StandardScaler, most of the recommendations were saying that you should use StandardScaler before ...
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0answers
33 views

Normalize data with uneven groups?

I have a dataset with 3 independent variables [city, industry, amount] and wish to normalize the amount. But I wish to do it with respect to industry and city. Simply grouping by the city and industry ...
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0answers
13 views

Are there some resources for filters specifically applicable in big data applications? [closed]

Are there some resources for filters specifically applicable in big data applications? Particularly, are there major differences between filter design for other domains and filter design for data ...
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4answers
379 views

When should ordinal data be represented catigorically and when as integer?

I am doing the Kaggle competition House Prices: Advanced Regression Techniques to learn more about data analysis. I would like to apply multiple models to the data(Regularized LR, Random Forests, ...
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0answers
80 views

Input data for this dataset to be feed into keras for training

Suppose I have 3 csv files which forms the dataset for training a machine learning model in Keras. file1.csv ...