Questions tagged [data-mining]

Data mining uses methods from artificial intelligence in a database context to discover previously unknown patterns. As such, the methods are usually unsupervised. It is closely related but not identical to machine learning. Key tasks of data-mining are cluster analysis, outlier detection and mining of association rules.

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Distance function that captures both circular and "appear as line" clusters [closed]

based on what I know in k-mean clustering, if i use single linkage distance it can capture clusters of thread shapes but it is not suitable for capturing circular clusters. Also If we use complete ...
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32 views

Jenks Natural breaks - Interpreting Goodness of Variance Fit

I am trying to find breaks in a multiple continuous type variables. So, I tried the jenks natural breaks algorithm. Based on the code from here, I managed to find ...
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Cardinality of Hypothesis Space H

Assume I have the below dataset, features M and N are numerical, label is binary. M N Label 2 3 y 6 1 y 1 12 y 3 9 y 11 15 n 7 13 n 4 8 n 9 10 n My decision tree with binary split only has 1 ...
4 votes
1 answer
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Why do I get different results after shuffling data using DBSCAN

Sometimes, by simply shuffling my data, not changing the parameters, I get a different cluster result using sklearn.DBSCAN. Why this happens? I mean, by shuffling data, the data distribution is the ...
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What are exactly QSAR models?

I'm reading on the internet about QSAR models and I don't really understand what they are. I see some webs in which some data mining techniques like random forest, CART, etc., are mentioned. What are ...
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How do I build a decision tree model with a dataset that only has categorical values

kI'm trying to build a decision tree model on a dataset that only has categorical values, an example fragment of the dataset is below. My training dataset consists of 40 observations ...
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1 answer
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What is the purpose of cost function for Dynamic Time Warping

In Data Analysis, Dynamic Time Warping is a method to better speify the similarity between two time series: https://en.wikipedia.org/wiki/Dynamic_time_warping What is the purpose of introducing a cost ...
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Lift - Class ratio as actual randomness-measure

Context The Lift should show how a machine learning model performs better than randomness. Thus, a curve representing the ratio between the predicted class of a ...
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Pick minimum value based on MSE and point

I am attempting to automate some processes at work. Im familiar with statisical methods such as GLM, ANOVAs, Basic OLS, etc. But I am unsure of methods which I can use for this. problem statement: ...
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Clustering trends across categories: which one to use?

I have a dataset with daily temperatures for every country in 4 seasons: Spring, Summer, Fall, and Winter. I wish to group(cluster) countries with similar temperature trends across the 4 seasons. I am ...
2 votes
1 answer
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buy till you die - Discounted cash flow - NBD/GAMMA [closed]

I was learning about BYTD in an online tutorial here I understand that it is used a) to predict the number of purchases that will be made by the customer. b) Lifetime value of the cuatomer over a ...
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1 vote
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What statistical tests can I use to compare two different ml algorithm on a dataset that has been augmented using two different approaches?

I used SMOTE and ADASYN on a dataset separately and used Random Forest and KNN on them. Both giving quite close accuracy(RF= 97.75 %, KNN= 97.22% where SMOTE was used) & (RF=97.67% and KNN=97.42% ...
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silhouette score vs Distortion score

I am working on segmenting my customers with clustering. My dataset size is 7315 rows and 30 features. So, as a beginner to clustering, I passed all my 29 features (excluding id column) to the cluster....
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For the given data find the clusters. Assume the relevant parameters needed [closed]

Below is the given data, how can I make clusters using symmetric matrix?
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Explainable clustering for broker churn

I have a dataset like as below You can see that my dataset is longitudinal. There will be multiple records for the same broker with multiple or same customer, selling same or different products. Now, ...
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-1 votes
1 answer
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why random model response for X decile is fixed at X%?

I was reading online tutorials on lift and gain charts here, here, here In all of these tutorials, I read or see that random model curve is drawn with the expectation at each Xth decile, we get X% ...
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3 votes
2 answers
426 views

A universal measure of the accuracy of linear regression models

I have a dataset that contains both outliers and multicollinearity. I applied three different regression models to that dataset: ordinary least square, absolute linear regression, and Huber regression....
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Creating a binary attribute for each of the M nominal states

I am preparing for an exam in data mining and need help with the following question: Assume we have categorical data. One method to define a distance between two data objects is (p-m)/p where p is ...
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Dealing with class imbalance and data complexity issues

I am doing a classification task for a 5-class imbalanced dataset. Class distribution shows 2-majority & 2-minority clasess, as far: ...
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2 votes
1 answer
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Classification methods with only nominal attributes

I would like to know what classification methods can naturally deal with only nominal attributes. An example is decision trees created by C4.5. I imagine that other classifiers based on decision trees ...
1 vote
0 answers
171 views

How do non binary decision trees deal with categorical values that weren't in training?

I've been implementing Random Forest from scratch as a learning exercise. While most algorithms for decision trees seem to deal exclusively in binary yes/no questions, leading to binary trees, ...
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1 vote
1 answer
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Class separability and Overlap

I have a dataset for five different classes with 40 features. This dataset is somehow imbalanced with 2 majority & 2 monirity classes, the other somehow average. This is a classification task and ...
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Height limits relation to anomaly score in Isolation Forest

I am trying to implement the Isolation Forest algorithm in Python and faced an issue when dealing with the max_depth and the height limit (l) from the white paper. (See the 2. set height limit l) ...
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time series residual, seasonal and trend

I'm trying to understand time series Series = trend + seasonal + residual I read that centred moving average of period 'n' eliminated seasonal of period 'n' then CMA = residual + trend and I also read ...
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196 views

Local Outlier Factor (LOF) in Financial Time Series

I'm using Local Outlier Factor (LOF) in financial data with 40 features. When I use the algorithm I can achieve scores outliers, but I can't understand how I can get my algo to tell me the connection ...
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27 views

RMSE increases in test data while correlation also increases

I use deep networks to predict stock future return, and find that in the training data, the RMSE decreases and the correlation between label and the predection increases, which is normal. However, ...
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Is it the correct practice to remove highly correlated features before association rules mining?

I want to use association rules mining on a dataset (Apriori algorithm or FP growth algorithm). Although my data is not market basket analysis, I'm treating each row similar to a market basket, with ...
1 vote
1 answer
98 views

Statistical modeling vs data mining [duplicate]

What is the difference between "statistical modeling" and "data mining"? I have searched the internet, but I can't see it clearly. Is there any overlap? Can they be considered ...
1 vote
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Data mining for gene dataset with pairwise comparison [closed]

I have a table of sample a b c's gene data pairwise comparison, but I really don't know how to start data mining for this specific dataset. I wonder if anyone can come up with some idea, maybe in some ...
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Is linear regression appropriate for this analysis ? what additional operations to do?

I haven't done statistics / econometrics for a long time. I haven't done a lot by the way. But I would like advice on some methods and tests to be performed on two excel files that I have. Each excel ...
1 vote
1 answer
515 views

How To Determine Number Of Clusters In T-SNE And Best Clustering Algorithm?

I used TSNE method to cluster my DataSet. ...
4 votes
1 answer
273 views

What is the purpose of conducting Simple Random Sampling WITH Replacement?

Part of data preparation is simple random sampling. Random sampling can be of two forms with replacement or without replacement. With replacement, subset sampling simply might contain duplicates of ...
1 vote
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24 views

How autocorrelation work based on the data plot?

Let's suppose we have a time series is a=[1,1,1,3,3,3,1,1,1,3,3,3] as then the autocorrelation figure for this time series is The lag here is 4, for lag = 1, the autocorrelation is between [1,1,1,3,...
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What does the meaning of the autocorrelation in this picture?

From this figure, how should I understand what is the lag on the top figure? and when in the bottom figure for example the autocorrelation is 0.45 what does tell us about the above figure? Another ...
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Applying ML to Diagnostic Analytics on Financial Report

Background: We (a team in the IT department) are currently helping the financial team solve their problem, by automating their tasks. The task is this: they review the financial report monthly and ...
3 votes
2 answers
232 views

What is the difference between p-hacking and data mining bias?

From my understanding, data mining bias occurs when someone repeatedly searches through a data set to find statistically significant results. How is this any different from p-hacking? What is the ...
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How to compare the peformance of different clusterings without true labels

Firstly, I know some scores like silhouette score and Davies–Bouldin score to compare the performance in one clustering method. However, I am not sure how to compare results in different clustering ...
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1 vote
1 answer
31 views

How to Find out the Best Way to Encode Data in ML?

I have been thinking in this problem for quite a while, I cannot figure out a way of knowing, (based on the task) what will be the best data encoding I can do for training the model. Imagine I have a ...
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19 views

How to best visualize time interval difference and compute a single measure

I have a table like as shown below ...
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2 votes
1 answer
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Visualizing shared instances of p-values<alpha across large numbers of treatments

Assume a data table that presents the p-values of a large number of independent runs of a statistical hypothesis test. Each run represents a single test with two possible hypotheses (i.e., null and ...
2 votes
1 answer
35 views

How to make a decision - when there is a tie and no human expert

We have two algorithms (simple rule-based) working on labeling the dataset as "Yes" and "No" for a disease. There is no ML involved in this task. For ex: If Algo 1 says subject 1 ...
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0 votes
1 answer
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Find all possible clusterizations

I need help to find all possible clusterizations via the k-means method in Python. Let's assume for simplicity that I have the following table: height | weight | country of origin (X/Y/Z) | flag (1/0) ...
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the ratio of validation set and test set should be equal?

I always heard that the common ratio of the train:validation:test is 70:15:15 or 80:10:10 or 60:20:20, sounds like the validation set and test set should be equal size. Assuming that I wanna use 5 ...
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40 views

Machine Learning for choosing the right cover box to contain smaller item boxes

I am studying on choosing the right box to contain item boxes. When customers order items, items have their own cases and ordered items are packed with the right cover box to contain them to deliver. ...
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How can I do one class learning for outlier detection?

I understand I can use various sampling techniques when dealing with imbalanced datasets. However, I wonder how I can build a classification model from the training dataset only including data that ...
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2 votes
1 answer
75 views

Why does my model produce unrealistic output?

I am trying to run a binary classification problem on people with diabetes and non-diabetes. For labeling my datasets, I followed a simple rule. If a person has T2DM...
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1 vote
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If base classifier is stable then error of ensemble is caused by bias in base classifier. Why?

I'm reading the book- Intro to Data Mining by Pang-Ning Tan. Under "Bagging" it's written: If a base classifier is stable, i.e., robust to minor perturbations in the training set, then the ...
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A space of functions and their Fourier Transforms?

Conjugate variables and the Fourier transform are often used to analyze different states of a single object. For example in Quantum Mechanics it can be used to describe changing information about ...
2 votes
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Understanding the determination of principal components

The idea of PCA is to find the directions (in high dimensional space) in which the essential structures (with regard to large variance, scatter) of the data lie. The assumption is that original ...
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How can i cite Sequential Forward Feature Selection (SFFS)?

I've seen many papers/books about this technique but none cite its author. Is it ok to cite any machine learning theory book that explains it? Thanks.
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