Questions tagged [localoutlierfactor]

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How to improve F1 score with LocalOutlierFactor

The classification we are working on is to predict the investment strategy the company is using by NLP, and there are four types of strategy. “Balanced Fund (Low Risk)”, “Fixed Income Long Only (Low ...
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LOF vs k-NN in data with varying density

When the dataset is comprised of regions of varying densities, which technique is more effective for outlier detection Localised Outlier Factor(LoF) or K-Nearest neighbors (KNN)
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AUC measure for Local outlier detection in python?

I'm using Local outlier factor algorithm provided by Scikit-learn for outlier detection. For the evaluation i want to use auc measure. ...
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Why is One Class SVM predicting that half my dataset consists of outliers?

I am currently working on a dataset with 14 continuous features, a categorical target over five classes, and 90,000 samples. My current goal is to explore outliers in the dataset, and to that end I ...
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Anomaly detection on high dimensional Data using k means/SVM/LOF? [closed]

I am working on one Anomaly detection problem (unsupervise problem) Data set have 1) 15 columns and around 8k rows , including normal and abnormal(outlier ) rows, without label , all are numeric ...
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When forecasting, is it better to remove the outliers or just to transform them?

I am forecasting the number of logins. I have a dataset with the number of logins for each hour. First, I use LOF (local outlier factor) to find the outliers and then I remove them. Second, I use ...
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Should you normalize your training data for Local Outlier Factor

Say I'm using scikits implementation of Local Outlier Factor with euclidean distance being used by the reachability function. My input features are magnitudes apart, so is it advisable that I ...
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LOF (Local Outlier Factor) choosing the value of k

Just want to understand one thing. Let's say for any data set I select k=20 and generate LOF for each point and then I show all the points in the descending order of its LOF. Now when I am analyzing ...
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Difference between identifying outliers using LOF and K-means clustering

I am identifying outliers using K-means and LOF (Local Outlier Factor). Let's say if we are identifying possible outliers using both the techniques, I believe LOF will pick global outliers also as ...
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