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 ...

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Analysis of small set of interview data using data mining techniques

I have 22 companies response about 22 questions/parameters in a 22x22 matrix. I applied clustering technique which gives me different groups with similarities. Now I would like to find correlations ...
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Lift Charts in Multiple Linear Regression

When lift charts are generated in a Multiple Linear Regression model, for example, in predicting a continuous variable such as price of a car, how can they be explained in evaluating the performance ...
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Can I split a table through the correlation of its 2 columns?

I've got a 2 column table (X, Y). Every row of the table says that the X on that row use the Y specified in the same row. This are the sample data. https://jpst.it/L6I5 I'd like to cluster the table ...
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How do apriori based algorithms avoid finding spurious relationships in their rules?

I'm taking a class on data mining and of course, we went over the Apriori algorithm (Fast Algorithms for Mining Association Rules). Something that I want to know is how do apriori based ...
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Outliers detection methods for RNA-Seq data

I have a rna-seq dataset with normalization in RPKM. The dataset have 1 gene per row with 4 different experiment condition. I need a detect de outliers values in this dataset. I used de weka filter ...
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Time Series Data Mining and Correlation guidance [on hold]

Introduction Editing this post to clarify what I am asking. This is a bit of a vague question to begin with. I am not asking if this particular statistics method with these variables will cause this ...
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Data science : where to find Project Examples using Python with SQL? [on hold]

I’ve learnt Python and SQL, but was suggested to “work in Python to analyze data sets stored in MySQL”. I am following CS109 which uses Python, but it does not really use SQL https://www.quora.com/...
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10 views

measure the inter-relationship among a set of multi-variate data points

Given a group of multivariate data points, are there any ways to formalize/quantify the relationship of one given point comparing to other data points in this group. Clustering maybe one approach. But ...
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statistics metrics or machine learning methods to quantify the relationship between a point and a group

There are several data groups: A1 = { A11, A12, A13, …, A1n} A2 = {A21, A22, A23, …, A2n} .. … … Am = {Am1, Am2, Am3, …, Amn} Here ...
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14 views

What is tolerance technique that use to deal missing data?

Current administrations of processing missing data can be approximately divided into three categories: tolerance, ignoring and imputation-based procedures. i- Missing data ignorance often refers to ...
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14 views

About installing Theano [migrated]

I hope this question is relevant to this community as Theano is increasingly a standard software to do machine learning. So I have been trying to follow the instructions here, http://deeplearning....
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undersampling-unbalanced data

what are the correct steps for undersampling in classifying models? for instance if a have an unbalanced dataset with 950 non event and 50 events I will undersample creating a dataset with a 50-50% ...
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Weka Decision Tree not working on real data

I'm trying to make human activity recognition using the iOS accelerometer and gyroscope. The feature that I use are mean, variance, standard deviation, energy and cross-domain entropy. If I provide ...
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1answer
43 views

Neural network library for Python for Microsoft Windows

I have been having trouble with selecting a good library for Neural network algorithms in Python. TensorFlow isn't supported on windows. Theano is still in the beta phase of development. PyBrain too ...
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1answer
20 views

Using different prediction models/algorithms for different subsets of dataset

Is there practice in data mining and machine learning where different parts of dataset are predicted using different algorithms/models? The logic is that some data samples are better predicted with ...
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8 views

Relational to Dimensional modelling

So, I currently have a relational database, supporting all the business logic of an application. I'm currently evaluating choices to build a basic, yet extensible, business analytics platform, and a ...
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1answer
18 views

Merging information of several events

I'm working in a database related to endometrium ultrasound. My DB contains several columns that may describe one or more injuries (scar tissues) by dimensions and volume: Injury1Height, Injury1Width, ...
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1answer
30 views

Which graph/network format should be used when releasing a data set?

Under RENOIR (an EU funded project) I am working on releasing the data set of Slovenian Press Agency for researchers and other folk. As part of the data set we will be releasing some graphs with ...
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4 views

Is it sensible to roll up the revenue predictions?

I have a general doubt on how to make predictions. for example: Scenario A: Predict revenue by (Year | Quarter) Scenario B: Predict revenue by (Year | ProductA | ProductB | ProductC | ProductD) ...
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27 views

Outlier/Anomaly detection in strings

Can anyone suggest methods/techniques to find anomaly in string data from database. The data contains road names, so every cell is unique. By outlier, I mean the strings with weird stuff(special ...
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29 views

Smart sampling techniques to ensure boundary/edge cases are included

In an effort to reduce the time it takes to test software against various data sets I would like to do create an application that looks at a data set and creates a "smart sample" from the it. The ...
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18 views

Implement decision support system for supermarkets using data mining

I am implementing a decision support system for supermarket managers using dataminig algorithms in C#, to make decisions based on how the expected sales would be vary with the change of given ...
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45 views

Creating training data for machine learning

I am creating a machine learning model but I don't have any data as such that can be used as training data. All I now that there are certain independent features/columns(categorical and numeric both) ...
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15 views

How can I apply subtree raising to this tree?

I am following a Data Mining course at the university and the professor give us this exercise: Apply subtree raising to the following tree how can I do this? thank you in advance...
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changepoint detection and its analysis

I applied changepoint detection provided by ecp package against a given time series. The time series plot marked with identified change points is shown as follows. ...
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How does Quest differ from, for example, C&RT or C5.0?

SPSS Modeler has implementations of a number of decision tree data mining algorithms. Some of them are relatively well-known, such as C&RT and C5.0, some slightly less so, such as CHAID and QUEST. ...
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Unbalanced classification problem: Can more data be more harmful?

In a two-class problem, I have 1000 raw data to train my model, which 900 belongs to class 1 and 100 belongs to class 2. If I add another 500 data into the pool but they all belong to class 1, will ...
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Difference between One Rule and Learn One Rule

What are the differences between One Rule and Learn One Rule? Learn One Rule goes deeper in the decision tree (and, like 1R, tests on all the attributes), is this correct? Thanks!
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1answer
21 views

How do I choose the appropriate numbers of customers to be considered for cluster analysis?

I am currently doing a customer segmentation project in SAS. I have identified 2700 customers who are have made a purchase in each of the 4 years I am analysing. For the cluster analysis the more ...
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13 views

Calculate drive time between two measure points based on timestamps, vehicle length and speed

The measure points logs each passing car with the following data: vehicle length (precision at about 10 cm), speed and timestamp. The distance between the sample points and speed limit is also known. ...
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23 views

How are the outcomes that generated from different predictive models combined to get more accurate predictions?

The simple average is commonly used to combine the predictions of different predictive models. Apart form the simple average, what are the other methods that can be used for combining the predictive ...
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33 views

Understanding Partial Correlation

I'm having some trouble fully understanding partial correlation and I was wondering if some of you can shred some light on my confusion. Let's consider the following scenario: It is a known fact ...
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12 views

How to measure the impact of a product on the global revenue?

We have products daily revenue and when each product started being sold by the company. We also have different break-down of product revenue by location, store, sales person, etc. We need to measure ...
2
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3answers
46 views

pattern recognition for sequence data

There are a lot of data sequences, I am trying to find pairs of sequences that are similar with other. Trivially, we can define some distance measure, and compare each pair of sequence in terms of ...
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10 views

Dataset with 20 real continous variables classification problem

I have a dataset of about 5000 records with 3 different possible labels/classes, furthermore, it has about 20 different attributes, all real and continous. my task is to find a classifier that ...
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24 views

Using spectral or hierarchical clustering for small world graph

Suppose we have a weighted edge graph with small-world property and we want to cluster the nodes of the graph based on the edge weights as similarity of nodes (the weight of an edge shows the ...
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7 views

Robuste classification of ground and no-ground points in dense forest LiDAR Airborne

This is my first project on my graduation so take easy. Im studying methods to remove outliers on LiDAR airbone data in the tropical amazon rainforest. Remove outliers above the trees is easy, the ...
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38 views

Decision tree implementation using ID3 algorithm (C# using AFrog.Net)

I am using ID3 algorithm to implement a decision tree and find an output for a given input query. For this I have a past data set and I am trying to implement the application as this code But ...
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Applying DBSCAN to a huge GIS dataset with a Haversine distance metric.

I have a training set (2GB) that contains GIS trajectory data for multiple taxi rides. I want to cluster the final destinations based on their spatial density and have therefore been trying to use the ...
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27 views

Number of parameter in a distribution and Accuracy

I have some data sets defining a random variable (already checked). and I tried to fit those data to different distributions. I have found a bunch of distributions that fit and have not been rejected ...
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18 views

Are scalability, parallelization and online learning the same?

Someone told me before that all of them are the same in machine learning algorithms. Is that right or not? Can an algorithm be scalable but can't be parallelized? Can it be parallelized but can't be ...
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39 views

Merge column vectors from the loop in to a single matrix *.mat in matlab [Solved] [closed]

I have an iteration of my algorithm and it gives me a column vector as a result (1899x1 double). I want to form a new matrix composed of these column vectors together sequentially (for example, the ...
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Herfindahl–Hirschman index for data accumulation

I'm checking the data accumulation in segments with Herfindahl–Hirschman index, the idea is to get segments with low index. Do you think this is a good way to detect this accumulation? and do you see ...
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30 views

Interpretation of a strange part in ROC curve

I generated the following ROC curve using Rapid Miner to compare few binary classifers but I don't know how to interpret the curve of "Random Forest" model It doesn't look like a curve
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3answers
34 views

how to predict sales of an item changes based on a discount given to another item?

I am developing a system where the management of the supermarket can make decisions on past sales data. There I mainly want to focus on how to predict sales of an item changes based on a discount ...
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Is the data visualization a sufficient indication for the separability of the data? What are the other indications of the data separation?

In other words, let's say we have a data representation as in the image below, which is generated from the PCA, the projection of the data onto the first two PCs. As it's shown in the 2-D space, the ...
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1answer
26 views

Is the likelihood statistic applicable for model selection in machine learning?

Minimising the likelihood ratio statistic is often used as a criterion for model selection in connection with linear and related models and statistics such as as AIC are an extension of this practice, ...