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H: Dummy coding a column in R with multiple levels
I have a dependent variable measuring the net revenue. One of the major predictor affecting this is "product" i.e. the product sold to the customer. My randomly sampled dataset contains 1.4 million entries.
Products are assigned a specific categorical value.
I feel th... |
H: ROC curves/AUC values as a performance metric
I want to plot ROC curves using R. I have a prediction matrix, where each column shows the prediction values corresponding to different approaches. Also, I have a label vector. The column names of prediction columns are ccs,badaI,badaII and the column name of label vect... |
H: group_by: How to Transform my Data
I'm coming from Stata and struggling to get used to group_by in dplyr. Perhaps using group_by is the wrong approach, but if you know Stata, you'll understand why I'm trying to use it (I think).
I'd like to transform the data as shown below:
Essentially, I'm trying to collapse eac... |
H: Outlier detection for unbalanced classes
I have to make a predictive model for predicting a boolean Won/Lost variable based on some other numeric data; and further find out the features of observations that have 'Won'.
However, the number of 'Won's' in my dataset is 0.05%. I've tried both oversampling and downsampl... |
H: When to use Linear Discriminant Analysis or Logistic Regression
The Wikipedia article on Logistic Regression says:
Logistic regression is an alternative to Fisher's 1936 method, linear
discriminant analysis. If the assumptions of linear discriminant
analysis hold, application of Bayes' rule to reverse the con... |
H: Overcome memory limitation when downloading from database into Orange
I would like to run the association rule mining algorithm of the Orange library on a dataset that is stored in a PostgreSQL database. The table 'buildingset' contains the itemsets for each user, thus each record is related to a user, and each fie... |
H: RNN vs CNN at a high level
I've been thinking about the Recurrent Neural Networks (RNN) and their varieties and Convolutional Neural Networks (CNN) and their varieties.
Would these two points be fair to say:
Use CNNs to break a component (such as an image) into subcomponents (such as an object in an image, such as... |
H: Hidden neuron representation of weights
In an RBM, if we represent the weights learned by the hidden units, they show that the neural net is learning basic shapes. For example, for the mnist dataset, they learn features of the numbers they are trying to classify.
In a regular feed-forward net with one hidden layer,... |
H: Does the count of items in a transaction matter to apriori?
When preparing my data for funneling into the Microsoft Association Rules algorithm, I was not sure if I should group by data by Transaction and Item, or have a record for every instance of an item in a transaction. Does the algorithm care and add weight i... |
H: When does cache get expired for a RDD in pyspark?
We use .cache() on RDD for persistent caching of an dataset, My concern is when this cached will be expired?.
dt = sc.parallelize([2, 3, 4, 5, 6])
dt.cache()
AI: It will not expire until Spark is out of memory, at which point it will remove RDDs from cache which are... |
H: Backprop Through Max-Pooling Layers?
This is a small conceptual question that's been nagging me for a while: How can we back-propagate through a max-pooling layer in a neural network?
I came across max-pooling layers while going through this tutorial for Torch 7's nn library. The library abstracts the gradient calc... |
H: Reshaping of data for deep learning using Keras
I am a beginner to Keras and I have started with the MNIST example to understand how the library actually works. The code snippet of the MNIST problem in the Keras example folder is given as :
import numpy as np
np.random.seed(1337) # for reproducibility
from keras.... |
H: Interpret User Interfaces with Machine Learning
I am currently working on a prototype of an application that should be able to interact with user interfaces.
Now every user interface has some common elements, like buttons, scrollbars, input fields etc.
I would like to use Machine Learning to "interpret" such user i... |
H: Determining correlated product categories using store purchase history
I have a large dataset that contains product purchase history, like so:
userID productID category subcategory
123 ABC Kitchen Knives
123 BEA Kitchen Organization
233 ZZS Electronics ... |
H: How would you teach multiplications to a neural network?
Let's say you train a neural network on Input = 1/Output = 2; Input = 4/Output = 8.
How would you train a machine to recognize that it needs to multiply the input by 2, from scratch?
AI: You need to limit the network model to one which naturally would general... |
H: NNDSVD to initialize Convex-NMF
I'm working with the Convex Nonnegative Matrix Factorization Algorithm described in Ding, Li, Jordan 2008 ("Convex and Semi-Nonnegative Matrix
Factorizations").
Good initialization strategies make all the difference and using the described k-means clustering to get started works very... |
H: Decision Stumps with same value leaf nodes
I'm doing some ADA boosting with Decision stumps and in inducing a binary classifying decision stump, i'm finding both leaf nodes to have a positive value. Can this be the case? Is this possible?
AI: What is the overall response rate? If it's low (even 15-20%) it may be di... |
H: Why does an L2 penalty prefer smaller and more diffuse weight vectors?
For instance, why is it that it is more favourable for a weight of [0.25, 0.25, 0.25, 0.25] (for which the L2 penalty is 0.25) instead of simply [1, 0, 0, 0] (for which an L2 penalty is 1)?
In this case, both weights would give the same dot pro... |
H: Predicting next action to take to reach a final state
Does anyone know of an algorithm that could be used to determine the next action to take to reach a desired state when trained on time-series data?
For example, a robot starts at a certain state, then takes an action to get to another state. This occurs continuo... |
H: Which features do I select from text?
Hello, I am very new to data science, machine learning, and stack overflow. Excuse me for being unclear or asking naive questions.
My question is as follows:
From any given document, I am trying to classify it according to the emotions it evokes in readers, using a neural ... |
H: What is the minimum size of the test set?
The mean of a population of binary values can be sampled with about 1000 samples at 95% confidence, and 3000 samples at 99% confidence.
Assuming a binary classification problem, why is the 80/20% rule always used, and not the fact that with a few thousand samples the mean... |
H: When should we consider a dataset as imbalanced?
I'm facing a situation where the numbers of positive and negative examples in a dataset are imbalanced.
My question is, are there any rules of thumb that tell us when we should subsample the large category in order to force some kind of balancing in the dataset.
Exam... |
H: Split a list of values into columns of a dataframe?
I am new to python and stuck at a particular problem involving dataframes.
The image has a sample column, however the data is not consistent. There are also some floats and NAN. I need these to be split across columns. That is each unique value becomes a column i... |
H: Recommendation model that can recommend already bought item
Most recommendation algorithms recommend new products to users.
If you bought this you might like that
But sometimes the item user is most likely to buy is an item that he bought sometime ago.
Is there any algorithm appropriate for this use?
AI: Usually... |
H: Unable to load NLTK in spark using PySpark
I have install NLTK and its working fine with the following code, I running in pyspark shell
>>> from nltk.tokenize import word_tokenize
>>> text = "Hello, this is testing of nltk in pyspark, mainly word_tokenize functions in nltk.tokenize, working fine with PySpark, plea... |
H: How can we evaluate DBSCAN parameters?
yes, DBSCAN parameters, and in particular the parameter eps (size of the epsilon neighborhood).
In the documentation we have a "Look for the knee in the plot".
Fine, but it requires a visual analysis. And it doesn't really work if we want to make things automatic.
So, I was wo... |
H: border_mode for convolutional layers in keras
Keras has two border_mode for convolution2D, same and valid.
Could anyone explain what "same" does or point out some documentation? I could not find any document on the net (except people asking that it be implemented in theano as well).
AI: With border mode "valid" you... |
H: Trying to figure out how to set weights for convolutional networks
I am working on CNN, and I have some doubts. Let's assume I only want one feature map, just to make things easier. And let's suppose my image is grayscale, to make things even easier. So, let's say my image is (32,32) --grayscale, hence just a chann... |
H: Term for relative recall
For in calculating success in information retrieval, precision and recall are fairly standard measurements, relating to accuracy of the results, and to what extent the results are comprehensive, respectively.
However, recall values typically require that you know how many correct results th... |
H: Question about bias in Convolutional Networks
I am trying to figure out how many weights and biases are needed for CNN.
Say I have a (3, 32, 32)-image and want to apply a (32, 5, 5)-filter.
For each feature map I have 5x5 weights, so I should have 3 x (5x5) x 32 parameters. Now I need to add the bias. I believe I o... |
H: Which, if any, machine learning algorithms are accepted as being a good tradeoff between explainability and prediction?
Machine learning texts describing algorithms such as gradient boosting machines or neural networks often comment that these models are good at prediction, but this comes at the price of a loss of ... |
H: Verification of trained system
I have trained a system in order to detect some features from a set of scenarios. Now the system can detect and classify that set. How can I validate how that system works in real world? What mathematics tools should I use?
AI: Did you also validate the data set with a separate test s... |
H: Difference between Validation data and Testing data?
I am bit confused about validating data. What is this data mainly for?? Like I am seeing some tutorial and they have some training[I know it] images , they they have some validation images[donot know] and some testing[I know] images? So what is validating images ... |
H: Modeling and Predicting Co-Occuring Values
I have data for a 100,000 people with different personality traits. Here would be sample data:
Person Trait-1 Trait-2 Trait-3 ..... Trait-N
John 1 0 1 1
I need a model where for a new user when I see Trait-X, I need a prediction ... |
H: Chose the right regression analysis
In R I have data where head(data) gives
day promotion profit new_users
1 105 45662 33
2 12 40662 13
3 44 46800 20
4 203 54102 46
Now day is simply the day (and is in order). promotion... |
H: Time Series Forecasting with Neural Network (mixed data types)
I have a dataset with the following format:
TimeStamp | Action | UserId
2015-02-05 | Action1 | XXX
2015-02-06 | Action2 | YYY
2015-02-07 | Action2 | XXX
...
I try to forecast future Actions for specific users based on the Users history in the dataset... |
H: Choosing regularization method in neural networks
When training neural networks, there are at least 4 ways to regularize the network:
L1 Regularization
L2 Regularization
Dropout
Batch Normalization
plus of course other things like weight sharing and reducing the number of connections, which might not be regula... |
H: Why are ensembles so unreasonably effective
It seems to have become axiomatic that an ensemble of learners leads to the best possible model results - and it is becoming far rarer, for example, for single models to win competitions such as Kaggle. Is there a theoretical explanation for why ensembles are so darn effe... |
H: Convolutional Neural Networks in R
I don't see a package for doing Convolutional Neural Networks in R. Has anyone implemented this kind of algorithm in R?
AI: I guess there is no package for cnn but you can write your own convolutional layer. mxnet or h2o will be useful for it.
check this out:
http://dmlc.ml/rstat... |
H: ValueError: Input contains NaN, infinity or a value too large for dtype('float32')
I got ValueError when predicting test data using a RandomForest model.
My code:
clf = RandomForestClassifier(n_estimators=10, max_depth=6, n_jobs=1, verbose=2)
clf.fit(X_fit, y_fit)
df_test.fillna(df_test.mean())
X_test = df_test.va... |
H: Dimension-Hopping in Machine Learning
What is the dimension hopping problem in machine learning (occurring in convolutional neural networks and image recognition)? I have googled about it but all I get is information on the Physics of material shape deformation. It will be more helpful to me if some one explain it ... |
H: Using Neural Networks To Predict Sets
I'm building a neural network for data analysis, however I'm stuck on how many output neurons I need and what they should represent. The neural network tries to predict peoples choices for certain objects. There are 75 possible objects, but here's the catch, they choose 6 of th... |
H: How to update bias and bias's weight using backpropagation algorithm
I'm writing my own training algorithm, but I don't know how to set the bias weight.
Have I to set bias in any layer?
Must the bias weight, be updated in every layer?
AI: There should be a bias weight for each virtual neuron as it controls the th... |
H: LeNet for Convolution network?
I keep seeing LeNet used to referring to a convolution network? I am wondering why LeNet is called LeNet? Is it the abbreviation of anything? Is there a difference between LeNet and convolutional neural network? Thanks!
AI: LeNet is a family (LeNet-1, LeNet-4, LeNet-5) of convolutiona... |
H: Compute Baseline/Representative of Time-Series Data
I have time-series data of 10-days for the same time interval as shown in below figure. Here it shows one-hour power consumption for 10 days. Data is sampled at 10 minutes rate.
I need to show this 10-day usage with a single baseline/representative curve. I can c... |
H: How to read Several JSON files to a dataframe in R?
I have a folder with 30,000 plus JSON file. A sample file with contents is posted below.
{
"name": null, "release_date_local": null, "title": "3 (2011)",
"opening_weekend_take": 1234, "year": 2011,
"release_date_wide": "2011-09-16", "gross": 59954
}
However, I n... |
H: Tips for a new data scientist
I am about to start a job in which I will be working with large datasets and will be expected to find trends, etc... I have found lots of resources on where to learn ML and other hard skills and feel that I am (semi) competent on this end.
I am interested in knowing if there are speci... |
H: generate graph from .eps file (preferably using R)
Using the R package 'Deducer', I saved a graphic (chart) as an .eps file.
I can open the .eps file, it's just a bunch of text.
How do I re-generate the graphic (chart) from the .eps file (preferably using Deducer or R)?
AI: EPS is "Encapsulated PostScript". Its mea... |
H: When to choose character instead of factor in R?
I am currently working on a dataset which contains a name attribute, which stands for a person's first name. After reading the csv file with read.csv, the variable is a factor by default (stringsAsFactors=TRUE) with ~10k levels. Since name does not reflect any group ... |
H: Sum up counts in a data.frame grouped by multiple variables
This is a snippet of the dataset I am currently working on:
> sample
name sex count
1 Maria f 97
2 Thomas m 12
3 Maria m 5
4 Maria f 97
5 Thomas m 8
6 Maria m 4
I want to sum up the counts grouped by name and sex t... |
H: Why do we calculate partial derivative of Error w.r.t output of Neural Network during backpropagation?
As seen in this image we calculate partial derivative of Error w.r.t output of the output neuron. Shouldn't it be normal derivative? Does not that particular error is determined by only that output?
AI: The parti... |
H: Time-stamp for linear model
How can we extract information from time-stamp variable for modelling? I have a variable with format mm-dd-yyyy hh:mm:ss I want to predict an outcome variable using time-stamp as input variable. I do not think i can directly use this column for modelling and will need to do some transfor... |
H: Account for unknown error in time series data
Given:
Time series data collected from sensors.
There is an unexpected gradual drop in the initial data when sensors are idle.
However, this drop is not so visible when sensors are active because the drop is masked by the actual measurements.
Main question: How do I el... |
H: Redundancy - is it a big problem?
I am trying to create a sentiment analysis program which will classify some of the tweets which i have collected under a hashtag. There are 7750 tweets in the dataset and I am labeling them into the two classes now. Then I will use a neural network to classify them into positive an... |
H: Apache Spark Question
I am trying to parse the files using Stanford nlp in Spark in mapper function. How to set the number of mappers in Apache Spark? Please help me.
AI: It automatically determines the amount of mappers by the number of partitions your data is in. You can call getNumberPartitions on your data sour... |
H: Reading a wide dataset in R
I originally had a wide CSV dataset of about 18000 columns(and about 80 rows) that I am trying to read in R. It was stored in an Excel sheet,which unfortunately has a limit of only 16384 columns. Hence, taking the dimension I obtain:
> dim(train_set)
[1] 83 16384
i.e 1000+ columns a... |
H: Choosing the correct learning algorithm
I am kind of new to the data mining subject but i need help to choose a learning algorithm for my application:
The problem: identifying that a certain curve or data set belongs to a certain fault in a Component.
My training data should be like this:
Motor Current Values:
[0.... |
H: Technical name for this data wrangling process? Multiple columns into multi-factor single column
What is the technical name for the following data wrangling process? I want to collapse Table A into Table B. (To make the data suitable for ANOVA.)
Table A:
ArmyVet_ID Served_WW2 Served_KoreanWar Served_VietnamWar... |
H: Is there a text on Apache Spark that attempts to be as comprehensive as White's Hadoop: The Definitive Guide'?
Tom White's 'Hadoop: the Definitive Guide' has become a popular guide to the entire Hadoop ecosystem and earned a reputation as providing both a broad survey, as well as covering individual aspects of Hado... |
H: Scala vs Java if you're NOT going to use Spark?
I'm facing some indecision when choosing how to allocate my scarce learning time for the next few months between Scala and Java.
I would like help objectively understanding the practical tradeoffs.
The reason I am interested in Java is that I think some of my product... |
H: Machine learning technique to calculate weighted average weights?
I'm just starting to investigate machine learning concepts, so I'm sorry if this question is very naive, but I'm hoping that it will be an easy one to answer!
I have a document matching algorithm that individually calculates a match for each field (0... |
H: Looking for a rough explanation of additive hidden nodes and radial basis functions
I'm working on a neural networks project right now and for that I'm reading a bunch of scientific papers, in a few of those the terms additive hidden nodes and radial basis functions are thrown around, but I seem to have trouble to ... |
H: Match users based on the content of their articles
I have users in my database that I would like to match up or group togetter based on the content of there articles. I cant seem to find how this kind of problem is being solved today. Any advice will help.
Available Data:
1) Each user's posts (anything written by ... |
H: Newsgroup classification
Currently our company, has a special user forum.
The main forum is about specific topic: SIP protocol.
Im trying to understand what would be a good approach to classify the top 10 issues customers report in the forum,
Example:
Installation, Crash, Media, Database, etc.
What would be a goo... |
H: Optimisation strategy webstores with shipping costs
I am scraping the prices of several products on different websites for the past couple of weeks. These prices are stored, plotted and e-mailed to me every day with an update about the price changes. Now I want to take it to the next level, and make a store selecti... |
H: Using Neural Networks to extract multiple parameters from images
I want to extract parameters from an image using a neural network.
Example:
Given an image of a brick wall the NN should extract the width and height of the bricks, the color and the roughness.
I can generate images for given parameters to train the N... |
H: Master thesis topics
I am looking for a thesis to complete my master, I am interested in Predictive Analytics in marketing, HR, management or financial subject, using Data Mining Application.
I have found a very interesting subject: "Predicting customer churn using decision tree" or either "Predicting employee turn... |
H: Deep Learning for Time series
Deep Learning is an excellent model for classification problem such as image recognition or object detection. Can we use deep learning for regression problems - Time Series prediction ? So if it can, how can we build structure of deep learning. I mean how to building layer to extract f... |
H: Ideas for prospect scoring model
I have to think about a model to identify prospects (companies) that have a high chance of being converted into clients, and I'm looking for advice on what kind of model could be of use.
The databases I will have are, as far as I know (I don't have them yet), the list of current cli... |
H: First steps when analyzing a company's data
I'm not sure if this question is appropriate for this forum, so excuse me if it's not (if not, any suggestions on where might be a better place would be very much appreciated). I'm currently an undergrad in a quantitative field, and for the summer, I've been given an oppo... |
H: Difference: Replicator Neural Network vs. Autoencoder
I'm currently studying papers about outlier detection using RNN's (Replicator Neural Networks) and wonder what is the particular difference to Autoencoders? RNN's seem to be treaded for many as the holy grail of outlier/anomaly detection, however the idea seems ... |
H: Logistic regression on biased data
I am currently working on a dataset to predict customer attrition based on past data and transactions of the customers.
There are 2,40,000 customers in total out of which around 1,77,000 customers are active(as of today) while the remaining ones are inactive (6300).
This is how sa... |
H: Feature Selection and PCA
I have a classification problem. I want to reduce number of features to 4 (I have 30). I'm wondering why I get better result in classification when I use correlation based feature selection(cfs) first and then employ pca in comparison with just employing pca (the latter one is worse than t... |
H: feature redundancy
Why exactly does features being dependent on each other, features having high correlation with one another, mean that they would be redundant? Also, does PCA help get rid of redundant/irrelevant features or do we have to get rid of redundant/irrelevant features before running PCA on our dataset?
... |
H: how to choose classifer
is the best way to create the most accurate classifier to train a bunch of classifying algorithms like ANN, SVM, KNN, etc, and test different parameters to get optimal parameters for each classifier, and see which classifier has the least testing error?
Or is it better to use ensemble method... |
H: Feature Extraction - calculate slope
Having a bit of a mind-blank at the moment and am looking for some advice.
I am extracting features from time series data for input into a classification algorithm, for example I'm extracting average and variance from inputX.
For input Y, I have graphed the data and have seen... |
H: What does "linear in parameters" mean?
The model of linear regression is linear in parameters.
What does this actually mean?
AI: Consider an equation of the form
$y = \beta_0 + \beta_1x_1 + \beta_2x_2 + \epsilon$
where $x$'s are the variables and $\beta$'s are the parameters. Here, y is a linear function of $\be... |
H: How can give weight to feature before PCA
I wonder how can I give weight to my feature before employing PCA. I mean somehow weighted PCA. Because I know that one of the features is better than others and want to give importance to it in creating components (It is not possible to select only that feature. I should h... |
H: how to explain the behaviour: linear svm does better than non-linear RBF
I am working on a binary class classification problem.
Each sample is a vector 1x101, I have a lot of data samples more than 150k
I tried training a linear svm and a non-linear svm (RBF) "zscore normalization is used in both cases". surprisi... |
H: Approaches for implementing Domain specific Question answering System
Given several wikipedia articles on different movies.
What are the different approaches to implement a QA system to answer different quires related to movies.
Dataset : Wikipedia articles
Input : natural language query, eg : who directed term... |
H: Why is the number of samples smaller than the number of values in my decision tree?
I'm using scikit-learn RandomForestClassifier for a classification problem. When taking a closer look at one of the trees I noticed that the number of samples at the root was 662, but there were 507 instances of the first class and ... |
H: Which supervised learning algorithms are available for matching?
I'm working on a non-profit where we try to help potential university applicants by matching them with alumni that want to share their experience/wisdom and, at the moment, it is happening manually. So I'll have two tables, one with students and one w... |
H: What is this formula, related to simple linear regression, called?
This is my first post here. I hope I can make myself clear. Right now I'm learning linear regression as part of an introduction class to machine learning.
After going over the steps in the simple regression formulae, I realized that I had been doing... |
H: Machine Learning in Spark
I am using Apache Spark to perform sentiment analysis.I am using Naive Bayes algorithm to classify the text. I don't know how to find out the probability of labels. I would be grateful if I know get some snippet in python to find the probability of labels.
AI: Probability can be found for ... |
H: What's the difference between fit and fit_transform in scikit-learn models?
I do not understand the difference between the fit and fit_transform methods in scikit-learn. Can anybody explain simply why we might need to transform data?
What does it mean, fitting a model on training data and transforming to test data?... |
H: Characterisitcs of the data set for a binary classification problem
I want to build a classifier for my problem statement and for that I don't have data. So while doing data acquisition, what should be the minimum sample size? And would it be a good practice if I label each observation myself to build a valid data ... |
H: Understanding ROCs in imbalanced data-sets
A response variable (label) $B$ can either be $0$ or $1$.
In the training set, $B_i = 1$ is an extremely rare event at only $0.26\%$ occurrences. Which makes the prediction of this label on a test data-set a difficult problem.
I used SMOTE to sample from the training-set... |
H: Suggestions on what patterns/analysis to derive from Airlines Big Data
I recently started learning Hadoop,
I found this data set http://stat-computing.org/dataexpo/2009/the-data.html - (2009 data),
I want some suggestions as what type of patterns or analysis can I do in Hadoop MapReduce, i just need something to ge... |
H: Support Vector Classification kernels ‘linear’, ‘poly’, ‘rbf’ has all same score
I build a classification model based on SVM and getting same results after running different kernels. Can you please let me know if is mistake ? also recall for all are identical. Thank you for help.
Adding the location for the notebo... |
H: problem loading data into R
I have problem with loading data into R:
fileUrl <- "http://jadi.net/files/iran_it_status_1394_detail_data_jadi_net.tsv"
download.file(fileUrl , destfile="iran_it_status_1394_detail_data_jadi_net.tsv")
dev <- read.delim("iran_it_status_1394_detail_data_jadi_net.tsv",
head... |
H: Pruning and parameter reduction for decision trees
I am trying to perform a classification using a decision tree classifier. I was wondering whether using a Feature reduction method is relevant for decision trees since they automatically use pruning?
My idea would be to perform a loop from 5 to 15 parameter reduct... |
H: How to form Hessian matrix in BFGS Quasi-Newton Method
I came across this link. In BFGS Quasi-Newton Method, a Hessian matrix is used in weight updation. Is there any resource where I can find how this hessian matrix was obtained along with a clear description of the process, as to why Hessian matrix has been taken... |
H: What does it mean when people say a cost function is something you want to minimize?
I am having a lot of trouble understanding this. Does it mean you should not use the cost function very often?
AI: No, it means you are trying to find the inputs that make the output of the cost function the smallest. It doesn't me... |
H: How do I find the minimum distance between zip codes in R?
I have a dataset that lists all zip codes in the U.S., their types (standard, po box, university, etc). I want to replace po box and university zip codes with the next closest standard zip code. I broke down the dataset by state so that R wouldn't have to m... |
H: feature selection techniques
Is it always a good idea to remove features that have high mutual information with each other and to remove features that have very low mutual information with the target variable? Why or why not?
AI: Doing that is a very good idea. The problem is that doing that is very hard.
Feature s... |
H: How to reduce time R takes for model building
I am building machine learning algorithms in my laptop. It has i3 procesor and 16 GB RAM. Despite using multiple cores(3 out of 4), it takes 2 days to run all the techniques that i am trying to run an obviously data is huge (close to 1.3 million rows and 20 variables).
... |
H: How does QUEST compare to other decision tree algorithms?
SPSS Modeler has an implementation of QUEST, along with C&RT, C5.0 and CHAID. QUEST is relatively rarely covered in textbooks - what are its pros and cons compared to other decision tree algorithms? How does it make splits? Why is it (apparently) not in as w... |
H: Convert Lat /Lon of User input to Lat/Lon of Open Data
I have data from a public data set in gridded form 2.5 degree x 2.5 degree(lat,lon).
Latitude goes from 90 N to -90 S. Longitude goes from 0 to 357.5. It is stored every 2.5 degrees and there are no intermediate values.
My user will want to download data from... |
H: Feature selection for gene expression dataset
I am searching for a feature selection algorithm which selects features that are:
relevant to discriminate groups of samples (for each sample a group label is provided)
endowed with high variance across all the samples
This should be applied to gene expression dataset... |
H: Analytics term for turning row values into column names and count its assigned values
Do we have a data mining/analysis term for turning row values into column names and count its assigned values?
AI: Aggregation.
See Aggregate function |
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