Questions tagged [outlier]

For questions regarding outliers or unusual points in the data.

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548 views

Why labels are not used in outlier detection algorithms?

I read this article from sklearn: https://scikit-learn.org/stable/modules/outlier_detection.html While these algorithms are very useful for outlier detection, I'm surprised to see that they are not ...
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2answers
379 views

Explainable anomaly detection

There are plenty of working for explaining prediction in supervised learning (e.g. SHAP values, LIME). What about for anomaly detection in unsupervised learning? Is there any model for which there ...
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1answer
37 views

Functions in scikit that detect outliers automatically?

I know a way to visualize outliers is to make a box plot, but wanted to know if scikit had any quick ways to detect outliers for each variable?
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2answers
6k views

How can I replace outliers with maximum non-outlier value?

I am doing univariate outlier detection in python. When I detect outliers for a variable, I know that the value should be whatever the highest non-outlier value is (i.e., the max if there were no ...
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3answers
367 views

Standard deviation as outlier detection

I have a quite basic question: A standard deviation is defined such that around ~66 % of the data lies within it. And around ~99 % within three standard deviations. When I wanna' use the standard ...
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2answers
70 views

How to improve identification of outliers for removal

I have many datasets where the measured value is either "normal" (i.e. the process is running" or abnormal (i.e. process is not running). Unfortunately, I don't have a measurement that clearly ...
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1answer
90 views

How to convert a non gaussian distribution into a gaussian destribution?

Suppose I have a dataset inwhich there are few dimensions that distribution over them is non gaussian and this means, skewness is nonzero (possitive or negative). This is caused by some outliers in my ...
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0answers
20 views

Machine Learning alternative for hashing

Is there a Machine Learning technique that can used to detect the slightest change in data? I know this can be done using a hash but I was just wondering if there is any machine learning technique out ...
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1answer
35 views

Which is the correct method for outlier analysis on a dataset for modelling?

I'm trying to build a regression model but my data-set have many outliers points which I need to analyze and then remove them. There are two ways to do it, 1) First do all the analysis on every ...
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1answer
376 views

Isolation forest - grouped by

I'm trying to use isolation forest algorithm for outliers detection. Data has 2 columns: id and REV. Below code gives me ...
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1answer
3k views

In elbow curve how to find the point from where the curve starts to rise?

I am computing a distance metric on my data. The result is then being sorted in ascending order. The samples having distance more than a specific threshold are to be marked as outliers and will be ...
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1answer
303 views

Dealing with new outliers after capping

I'm trying to cap outliers in a column of my pandas DataFrame. Here's the boxplot for a column of my original data. So, using code from this stackoverflow answer, I tried capping outliers. Here's ...
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0answers
55 views

How can detect and highlight outliers by using gaussian function and normalize the data elegantly?

I tried to normalize the data by using Gaussian function 2 times on both positive and negative numbers of each parameter of this dataset. The dataset includes missing data as well. The problem is I ...
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0answers
56 views

unsupervised outliers detection - possible solution?

I have dataset of traders' transaction data: trade id, date, stock id, sector of stock id, buy-or-sell, volume $ The goal is to identify anomalies in transactions data of traders. For example to ...
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1answer
3k views

Isolation forest sklearn contamination param

I'm working on an unsupervised anomaly detection task on time series using isolation forest algorithm. I'm developing in Python, more in detail using sklearn. I found out a lot of examples on this, ...
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3answers
149 views

What is meant by outliers in text data set. How to detect them?

I know that outliers are present in data but their behaviour varies a lot from remaining data points. But today while learning about naive-Bayes they mentioned that naive-Bayes can affected by the ...
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3answers
18k views

How to remove outliers using box-plot?

I have data of a metric grouped date wise. I have plotted the data, now, how do I remove the values outside the range of the boxplot (outliers)? All the ['AVG'] data is in a single column, I need it ...
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3answers
56 views

good algorithm for outliers detection

I have 2 independent data sets (1. 300 rows and 2.3000 rows) with 6 months trades observations for 50 traders. In both datasets I have: trader id, stock title, buy/sell volume, date of trade, sector ...
2
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1answer
159 views

Number of Nodes in Isolation Forest

I am currently reading this paper on Isolation Forest. At page 3, there is a definition of Isolation Tree and there are a couple of sentences that I don't understand: Given a sample of data X = {...
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5answers
4k views

Time Series:Outlier Detection

I have time series data which looks like the graph mentioned below. I am familiar with the method of removing outliers based on the standard deviation and median values. Drawback of these methods are ...
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5answers
805 views

Methods to detect this kind of outliers

Background I don't know much about (or to say anything) about data science or machine learning. But I'm interested in learning and thought this problem can be solved with machine learning. That's why ...
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2answers
372 views

How to scale outputs from AutoEncoder from multiple models?

I have a problem for which I have not been able to find any answers in my search so far. BACKGROUND I am working on an anomaly detection problem on machines utilising an auto-encoder. I am building ...
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1answer
50 views

How to distinguish between normal fluctuation and outliers in ARIMA model?

I have a dataset about sales per day of certain products at the ITEM/DAY/STORE level , I've plotted the series and visually examined it for any outliers, volatility, or irregularities. And this is ...
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1answer
39 views

Clustering unbalanced dataset

The data I am working on has some really large price values and some really small values. What I did was first perform feature bagging on the data and got them labelled to (0,1) and then did ...
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2answers
107 views

Outlier detection for Disk Space Usage

I would like to do outlier or anomaly detection on the disk free space data. Sample dataset as below (I don't have any label dataset): ...
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2answers
70 views

A Proper Outlier Detection For the Attached Figure

I am wondering how I could detect the red points as outliers using an algorithm (best method for this scenario) not through visualization since it is clear that they are outliers in the figure. ...
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0answers
56 views

How to find anomalies/outliers in Panel Data?

I have panel data based on 900000 different entities with 384 time steps and the data is not normally distributed. I am looking for outliers/anomalies, this is unsupervised as I have no examples of ...
1
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1answer
108 views

Isolation Forest: simple example

Can some one please explain Isolation Forests more clearly? Everywhere I search, I find the same explanation: Isolation Forest ‘isolates’ observations by randomly selecting a feature and then ...
2
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1answer
80 views

Replacing mean by median over batch-size to lessen the impact of outliers

In the case of training a Neural Network on a regression task. Assuming the data has a significant amount of outliers. Provided that the error needs to be RMS and not MAE. Can it be better (as in less ...
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1answer
199 views

Algorithm suggestion for anomaly detection in multivariate time series data

I have time series data containing user actions at certain time intervals eg ...
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2answers
120 views

How to visualize change in a distribution with a few outliers that account for a very large percent of the total?

I'm working on an edtech product where some of our traffic lands on webpages about textbooks. Textbooks belong to subjects like Algebra, Calculus and Spanish. In each of our subjects, we have "...
7
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1answer
691 views

How to decide how many n_neighbors to consider while implementing LocalOutlierFactor?

I have a data set with rows: 134000 and columns: 200. I am trying to identify the outliers in data set using LocalOutlierFactor from scikit-learn. Although I ...
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0answers
98 views

What’s more appropriate for outlier detection? Classification or Regression?

I'm using PyTorch and i’m working on a data set where I only care about “outliers” from the norm. The data is comprised of long time series with gaussian distribution, while once in a while there is a ...
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2answers
256 views

which outlier detection technique?

I'm new to data science. I have a question on anomaly detection techniques. There are several anomaly detection techniques such as statistical, density based, depth based, clustering, etc.. Given a ...
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1answer
69 views

Gracefully removing observations with outliers in N fields

I have a function. ...
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1answer
359 views

Is there any formal explanation for the sensitivity of AdaBoost to outliers?

AdaBoost is known to be sensitive to outliers & noise. However, the explanation seems to be hard to found or nontrivial.
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2answers
2k views

Effect of outliers on Naive Bayes

Are Naive Bayes algorithms affected by outliers in the data? Suppose there is a data set, does one need to remove outliers before applying Naive Bayes?
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3answers
2k views

Why is Local Outlier Factor classified as Unsupervised if it requires training data with no outliers?

In Scikit-Learn, the Local Outlier Factor (LOF) algorithm is defined as an unsupervised anomaly detection method. So then I don't understand why this algorithm requires pre-filtered training data. ...
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1answer
580 views

Outliers handling

I have a large dataset of >100 columns with nearly all types of data. I want to remove outliers from my dataset for which purpose I've decided to use IQR. Problem is even when I apply quantile of 0.25/...
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3answers
2k views

Should I remove outliers if accuracy and Cross-Validation Score drop after removing them?

I have a binary classification problem, which I am solving using Scikit's RandomForestClassifier. When I plotted the (by far) most important features, as boxplots, to see if I have outliers in them, I ...
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1answer
93 views

Anomaly detection in nominal big data

I have to apply an anomaly detection algorithm on big data, the values of each column on my dataframe are nominal and vary over 10000 times, the algorithms I've found only accept numeric values, is ...
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1answer
60 views

Finding outliers from multiple files [closed]

I am dealing with a very strange problem. I have a lot of files. I need to show which files are similar and which one has exception/outliers using its data. I can show with unsupervised learning ...
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1answer
52 views

Cleaning the univariate dataset with high noise

At this time, I am having a dataset containing the operating duration for some sensors. This could be considered as a univariate dataset because it has only 1 dimension. For example: ...
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2answers
196 views

Best way to deal with realistically imbalanced dataset for Regression problem

I have a dataset where each object has a label between 0-1. Objects with label = 1 are very common but those with label = 0 are very rare. I am interested in predicting the label in unseen data. NOTE:...
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0answers
24 views

Practical examples/tutorials of using One-Class Support Vector Machines

I am a newbie in machine learning, and hope to solve an anomaly detection task using One-Class Support Vector Machines (OCSVM). ...
2
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1answer
908 views

Collinearity and Outlier Removal

I am playing with a credit fraud detection dataset at Kaggle. An imbalanced dataset with about 0.1% of fraud transaction. The features are 28 PCs out from a PCA exercise done by the data publisher + ...
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1answer
900 views

Which order is correct Feature Selection then Outlier Detection or vice versa?

which of these orders is correct? First (Feature Selection) Second (Outlier Detection) or First (Outlier Detection) Second (Feature Selection)
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3answers
2k views

How to use Autoencoders for outlier detection on images

I have a bunch of images taken from a camera showing a pipe and would like to detect if the pipe is leaking or not. There are very few examples of leaking pipe in the data set. So considering this ...
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1answer
75 views

Is there an upper bound for k in nearest neighbors-based methods?

When applying a nearest neighbors-based method to a data of, for instance, 2000 points, what is the largest number of neighbors that can be considered ? I am using a nearest neighbors method in an ...
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2answers
118 views

How to make multiple regression perform better for outliers? (without reducing effect of them)

I have a small dataset(about 60 samples) and I need it to predict well for high target values. There are only a few high values and all models I tried perform poorly for these high values. So I ...