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H: What is the difference between SVM and GMM classifier What is the difference between support vector machine and Gaussian mixture model classifiers? AI: A Gaussian mixture model is a special case of a mixture distribution, which is a simple way of combining probability distributions. However, the SVM does not make a...
H: finding maximum depth of random forest given the number of features How do we find maximum depth of Random Forest if we know the number of features ? This is needed for regularizing random forest classifier. AI: The maximum depth of a forest is a parameter which you set yourself. If you're asking how do you find th...
H: How do scientists come up with the correct Hidden Markov Model parameters and topology to use? I understand how a Hidden Markov Model is used in genomic sequences, such as finding a gene. But I don't understand how to come up with a particular Markov model. I mean, how many states should the model have? How many po...
H: Can I consider this pattern of data as a linear and use parametric multiple linear regression? In the data, there are 355 observations including one continuous dependent variable (Y: ranges from 15-55) and 12 independent variables (continuous, categorical, and ordinal). The X1 (2 levels) and X6 (3 levels) are consi...
H: Examples of the Three V's of Big Data? What are some examples of the Three V's of Big Data? The three V's stand for: volume, velocity, variety. Reference: Three V's of Big Data, provided by Norwegian University of Science and Technology. https://www.ntnu.edu/ime/bigdata/what-is AI: Volume: Simply stated, big data i...
H: Sentiment Analysis Tutorial I am trying to understand sentiment analysis and how to apply it using any language (R, Python etc). I would like to know if there is a good place on internet for tutorial that I can follow. I googled, but I wasn't very much satisfied because they were not tutorials but more of theory. I...
H: Predict which user will buy with an offer - discount I have historical data from an e-shop transactions. I want to write a prediction model and check if a specific user will buy with or without a discount, so I can do some targeting offers. The idea is: If a user will buy the regular price, will not have an offer....
H: Sampling for multi categorical variable My hypothesis h depends on multiple categorical variables (a,b,c) each with their corresponding set of possible values (A,B,C). Now each of my data point exist in this space where I have no control over the values (observational data). For e.g. Hypothesis to predict user sh...
H: Scan-based operations Apache Spark Looking at the first paper on RDDs/Apache Spark, I found a statement saying that "RDDs degrade gracefully when there is not enough memory to store them, as long as they are only being used in scan-based operations" What are scan-based operations in the context of RDDs and which of...
H: Cosine Distance > 1 in scipy I am working on a recommendation engine, and I have chosen to use SciPy's cosine distance as a way of comparing items. I have two vectors: a = [2.7654870801855078, 0.35995355443076027, 0.016221679989074141, -0.012664358453398751, 0.0036888812311235068] and b = [-6.2588482809118942, -0...
H: Optimal projection for data visualization I have 90k points in $\mathbb{R}^{32}$ (i.e., a 90k by 32 real matrix) which I want to visualize. I know I can cluster my points (k-means &c), but I want to select a few "interesting" 2-planes in $\mathbb{R}^{32}$, project the points there and scatter-plot them. How do I se...
H: Extract the "path" of a data point through a decision tree in sklearn I'm working with decision trees in python's scikit learn. Unlike many use cases for this, I'm not so much interested in the accuracy of the classifier at this point so much as I am extracting the specific path a data point takes through the tree ...
H: How can I vectorize this code in R? Maybe with the apply() function? I am really struggling to replicate the output of the dist() function in R code without using 1 or 2 for loops. (If you're wondering why I'm doing this, it's so that I can play around with the distance calculation, and also to improve my R skills ...
H: Why does ada (adaboost) in R return different training error graphs and variable importance plots when running the same function multiple times? Question says most of it. I created a matrix of descriptors, set the vectors of responses, and input a set number of iterations. Each time I run the function with the same...
H: R: Revalue multiple special characters in a data.frame R noob here.. I have the following data frame >data Value Multiplier 1 15 H 2 0 h 3 2 + 4 2 ? 5 2 k where the multiplier is of class factor. The values of K & k is 3, + is 5 and ? is 2. I have used > data$Multiplier <- revalu...
H: Why would removing a variable in adaboost decrease error rate? I was trying to classify an outcome on some data using adaboost (the ada package in R) and I was playing around with the training data set of descriptors when I realized that removing a column in the descriptor matrix increased the accuracy of the outpu...
H: Reason behind choosing Neural Network for classification Given a two class multi dimensional classification problem, what reason would you give to choose Artificial Neural Network for carrying out the classification instead of Support Vector Machine or other classification methods? AI: SVM is Parametric. Parametric...
H: On fitting a Poisson distribution to make sense of data Hi guys I am working with a regular network which has the shape of a square grid and contains 100x100=10000 nodes. The edges (links) between these nodes simply follow the shape of a chess table: each node which is not placed in the corner or along the boundary...
H: Using Machine Learning to Predict Musical Scales It's possible to use Machine Learning techniques to cluster songs into musical-scale groups? I mean: "this song was written in C"... or "this song was written in Am" etc. I made a fast search about the subject and I found no software that can do this. If you know som...
H: Reduce dimension, then apply SVM Just out of curiousity, is it generally a good idea to reduce the dimension of training set before using it to train SVM classifier? I have a collection of documents, each of them is represented by a vector with tf-idf weight calculated by scikit-learn's tfidf_transformer. The numbe...
H: Extracting list of locations from text using R I have a string containing many words [not sentences], I want to know how I can extract all the words that correspond to a location in that string for example: text<-c("China","Japan","perspective","United Kingdom","formatting","clear","India","Sudan","United States of...
H: Appropriate algorithm for string (not document) classification? I am trying to classify a large-ish number of small strings (millions) into about 10 disjunct categories. Examples of classes and strings for each class include: email: "foo@bar.com" phone: "55", "22334455" personName: "John", "Q.", "Public" organizati...
H: Agglomerative Clustering Stopping Criteria I am trying to implement section 3.4 of paper Predicting Important Objects for Egocentric Video Summarization where they have created a distance matrix of frame histograms. In short, let say Ω is mean of distances between all frames,DVis distance matrix. I didn't understan...
H: One multilabel classifier or one for each type of label? Let's say I need to classify addresses with scikit-learn, so if I want my classifier to be able to classify addresses by the street name, and post/zip code, should I do a OneVsRest classifier, or separate them into two different classifiers (for the same trai...
H: How to visualize data of a multidimensional dataset (TIMIT) I've built a neural network for a speech recognition task using the timit dataset. I've extracted features using the perceptual linear prediction (PLP_ method. My features space has 39 dimensions (13 PLP values, 13 about first order derivative and 13 about...
H: Steps in exploratory methods for mild-sized data with mixed categorical and numerical values? Experienced in signal/image analysis, and new to data science, I recently was challenged with a relatively simple dataset: 100 to 200 items, about 10-20 numerical variables (in the [0-1] or percentage range), with only one...
H: Yarn timeline recovery not enabled error upgrading via ambari Using the automated upgrade, when I try to upgrade I get: “YARN Timeline state preserving restart should be enabled Reason: YARN should have state preserving restart enabled for the Timeline server. The yarn-site.xml property yarn.timeline-service.recove...
H: how often should one sample a dataset? I have some archive data that show the variation of a certain quantity X measured over 1-year intervals. I'm now facing the problem of understanding how X correlates with another variable Y, that I can measure much more frequently, even daily. So my question is, is it really n...
H: Multivariate linear regression in Python I'm looking for a Python package that implements multivariate linear regression. (Terminological note: multivariate regression deals with the case where there are more than one dependent variables while multiple regression deals with the case where there is one dependent var...
H: Classification when one class is other I am working on a litigation support application using the Enron corpus, which contains about 600,000 unique text documents. In litigation, one is often concerned with whether a document is responsive or non-responsive. One produces responsive documents to the opposing side, u...
H: Memory efficient structure for membership checking without false positive The initial task can be described like this: I have a requirement to deduplicate HUGE list(potentially billions of items) without storing the original items - it's simply unaffordable All I need to know is answer to the question "Has my syste...
H: Unsupervised sequence identification I am looking for the best method to go from a sequence of events such as time event 1 a 2 b 3 a 4 b 5 c 6 d 7 c 8 d 9 e Where each letter corresponds to a certain event that occurs at a time. I want to reduce the number of events by aggregating frequently occurring events into ...
H: crow probability problem I am trying to solve the following problem, but am having some difficulty. Can anyone give me some guidance? There are lots of tourists in Grandeville. The streets in Grandeville run east to west and go from ..., S. 2nd St., S. 1st St., Broadway St., N. 1st St., N. 2nd St., ... The aven...
H: Predictive analysis of rare events I'm trying to predict rare events, meaning less than 1% of positive cases. I basically try to predict if a subject will have 0, 1, 2 ... , 6, > 6 failures (there are cases in all those categories). I've tried several algorithms: decision trees random forest adaboost grouping usin...
H: Python Seaborn: how are error bars computed in barplots? I'm using seaborn library to generate bar plots in python. I'm wondering what statistics are used to compute the error bars, but can't find any reference to this in the seaborn's barplot documentation. I know the bar values are computed based on mean in my ca...
H: Trying to understand Logistic Regression Implementation I'm currently using the following code as a starting point to deepen my understanding of regularized logistic regression. As a first pass I'm just trying to do a binary classification on part of the iris data set. One problem I think I have encountered is t...
H: Which algorithms or methods can be used to detect an outlier from this data set? Suppose I have a data set : Amount of money (100, 50, 150, 200, 35, 60 ,50, 20, 500). I have Googled the web looking for techniques that can be used to find a possible outlier in this data set but I ended up confused. My question is: W...
H: Is Vector in Cosine Similarity the same as vector in Physics? I'm new to Data Science. I'm trying to understand cosine similarity and it seems like the equation is about finding the distance between two vectors. From what I've Googled, a vector needs to have magnitude and direction. But in CS, it seems like it's a ...
H: SPARK 1.5.1: Convert multi-labeled data into binary vector I am using SPARK 1.5.1, and I have DataFrame that looks like follow: labelsCol, featureCol (Label1, Label2, Label 32), FeatureVector (Label1, Label10, Label16, Label30, Label48), FeatureVector ... (Label1, label 95), FeatureVector The first column is the l...
H: Does it makes sense to apply feature scaling on timestamp I was wondering if it makes sense to apply normal standardization on a feature like timestamp ? The data that I process are network packets. Thank you AI: For time series analysis. Yes But, turning data into a computable object for using in the ML computati...
H: Typing error handling n-gram character index and vector space model Suppose I apply tri-gram indexing for my document collection, and is implementing a vector-space model to help retrieving the document. In the text it is mentioned implementing a trigram will introduce a new step in filtering the result. However, w...
H: How to define a distance measure between two IP addresses? I have IP addresses as feature and I would like to know how much two IP addresses are similar to each other to use the difference in an Euclidean distance measure (in order to quantify the similarities of my data points). What tactic can I use for this? AI:...
H: Is there any difference between feature extraction and feature learning? It appears to me that "feature extraction" and "feature learning" are equivalent concepts, however there are 2 separate wikipedia articles dedicated to them that are notably different. In particular, only in the Feature Learning article Neura...
H: Predicting New Data with Naive Bayes Say I had the following training set for a Naive Bayes algorithm. Outlook Person Play Golf? ------- ------ ---------- Sunny Joe Yes Sunny Mary Yes Raining Joe Yes Raining Mary No Raining Harry Yes If...
H: Events prediction with time series of continuous variables as features We have the feeling that behavior of a device in terms of continuous variables (fans speeds, temperatures, voltages, ...) has influence on rare events happening (components failures). I now have to build a predictive model for that, to proof the...
H: What is a benchmark model? I am working on a breast cancer dataset (http://kdd.org/kdd-cup/view/kdd-cup-2008). I need to perform classification on the data using C4.5 algorithm, after doing any necessary pre-processing. A section of the report that I have to write is "benchmark models" and I have no idea what that...
H: How to model compositional data? What is the best way to model compositional data problems? Compositional data is when each example or sample is a vector that sums to 1 (or 100%). In my case, I am interested in the composition of minerals in a rock and I have sensors that tell me the sum of the minerals but not th...
H: Understanding convolutional pooling sizes (deep learning) I'm dumb but still trying to understand the code provided from this e-book on deep learning, but it doesn't explain where the n_in=40*4*4 comes from. 40 is from the 40 previous feature maps, but what about the 4*4? >>> net = Network([ ConvPoolLayer(...
H: how to make new class from the test data I have a list of accounts as data set and I need to group the accounts that refer to the same user using many features. I'm thinking to use machine learning( but I'm new in this domain), because I know the group of each account for the training data set. ex of training data:...
H: On interpreting the statistical significance of R squared I have performed a linear regression analysis to two series of data, each of which has 50 values. I did the analysis in SPSS and as a result got a table which says that my adjusted R squared is 0.145 and its significance is 0.004. Being 0.004 < 0.05, I assum...
H: Examining a DocumentTermMatrix in RTextTools I created a DocumentTermMatrix for text mining using RTextTools. The rows for this DocumentTermMatrix correspond to dataframe rows and matix columns correspond to words. My question is : How can I get the words (labels vector) for examining the DocumentTermMatrix ? In...
H: Why do we need to use sysfunc when we call a SAS function inside a SAS macro I saw this piece of code in my project: %let num = test; %let x=%sysfunc(trim(&num)); Why could not I write: %let x= %trim(&num); Why did I need to use sysfunc? Under what circumstances can I call a function inside a macro without usin...
H: Feature extraction of images in Python In my class I have to create an application using two classifiers to decide whether an object in an image is an example of phylum porifera (seasponge) or some other object. However, I am completely lost when it comes to feature extraction techniques in python. My advisor convi...
H: Bagging vs Dropout in Deep Neural Networks Bagging is the generation of multiple predictors that works as ensamble as a single predictor. Dropout is a technique that teach to a neural networks to average all possible subnetworks. Looking at the most important Kaggle's competitions seem that this two techniques are ...
H: Finding the top K most similar sets I have a database containing sets of words. So for example, I have a database that has: {happy, birthday, to, you} {how, are, you} ... Given a query set, lets say {how, was your, birthday}, I want to find the top K sets in the database that is most similar to my query. Similarit...
H: With unbalanced class, do I have to use under sampling on my validation/testing datasets? I’m a beginner in machine learning and I’m facing a situation. I’m working on a Real Time Bidding problem, with the IPinYou dataset and I’m trying to do a click prediction. The thing is that, as you may know, the dataset is ve...
H: Best Julia library for neural networks I have been using this library for basic neural network construction and analysis. However, it does not have support for building multi-layered neural networks, etc. So, I would like to know of any nice libraries for doing advanced neural networks and Deep Learning in Julia. A...
H: Removing strings after a certain character in a given text I have a dataset like the one below. I would like to remove all characters after the character ©. How can I do that in R? data_clean_phrase <- c("Copyright © The Society of Geomagnetism and Earth", "© 2013 Chinese National Committee ") data_clean_df <- as...
H: Data Science conferences? This is a similar question like the Statistics Conferences question at CrossValidated What are the most significant annual Data Science conferences? Rules: Include a link to the conference Please include links for the talks (be it youtube, the conference site or some other video streaming...
H: How to place XGBoost in a full stack for ML? Is XGBoost complete by itself for prod-strength machine learning? If not, with which other tools or libs is it typically combined, and how? (I recently read a description of a stack that included ca 5 pieces, including XGBoost and Keras.) AI: Yes, it is a full-strength ...
H: Data Science Podcasts? What are some podcasts which are related to data science? This is a similar question to the reference request question on CrossValidated. Details/rules: The podcasts (the theme and the episodes) should be related to data science. (For example: A podcast which is about some other domain, with...
H: When do I have to use aucPR instead of auROC? (and vice versa) I'm wondering if sometimes, to validate a model, it's not better to use aucPR instead of aucROC? Do these cases only depend on the "domain & business understanding" ? Especially, I'm thinking about the "unbalanced class problem" where, it seems more l...
H: Deconvolutional Network in Semantic Segmentation I recently came across a paper about doing semantic segmentation using deconvolutional network: Learning Deconvolution Network for Semantic Segmentation. The basic structure of the network is like this: The goal is to generate a probability map in the end. I'm havin...
H: Reading a CSV using R I have a CSV file that, by all appearances, is totally normal except that each line ends with ,^M. Not sure if that has anything to do with my issue or not, but I try reading in the file in R with the usual command df <- read.csv('file.csv') and then when I try to inspect it by typing df it ...
H: pandas count values for last 7 days from each date There are two pd.DataFrame. First is like this: print df1 id date month is_buy 0 17 2015-01-16 2015-01 1 1 17 2015-01-26 2015-01 1 2 17 2015-01-27 2015-01 1 3 17 2015-02-11 2015-02 1 4...
H: Theoretical treatment of unlabeled samples In a typical supervised learning setting with a few positive and a few negative examples, it is clear that unlabeled data carries some information that can benefit learning and that is not captured in the labeled data. For example one can estimate mean values, bounds and s...
H: Dealing with big data I am on a project dealing with a lot of data in the form of images and videos (Data related to wind engineering). My requirement is to build a predictive algorithm based on the data I have. I have found many tools with which I can analyse the data where each tool has its own advantages and dis...
H: removing words based on a predefined vector I have the dataset test_stopword and I want to remove some words from the dataset based on a vector. How can I do that in R? texts <- c("This is the first document.", "Is this a text?", "This is the second file.", "This is the third text.", ...
H: Modelling population changes with years on a network graph This may be a silly question, apologies if it is. And further apologies if I've said something wrong. Network graphs, or visualisations look somewhat like this, with each node representing a thing connected to another thing. So for my example, I'd like to m...
H: Correlation and Naive Bayes I would like to ask if the Pearson correlation between fields (but not the class field) of a dataset affects somehow the performance of Naive Bayes when applying it to the dataset in order to predict the class field. AI: As you probably know, naive here implies that the "fields" are inde...
H: Hub removal from graphs I have a graph with vertices that represent some entities and the edges are weighted as the correlation between two such entities. I would like to break this graph into several subgraphs with high inner-correlation. My problem is that I have a few 'hubs', with high correlation to a lot of di...
H: How to cluster Houses on the basis of similarity of features+location? I have a dataset of houses like this: HouseID Latitude Longitude PriceIndex 1 1.4 103.120 1.21 2 1.42 103.112 2.01 I want to find houses which are similar to each other both on the basis of their position as...
H: Detecting boilerplate in text samples I have a corpus of unstructured text that, due to a concatenation from different sources, has boilerplate metadata that I would like to remove. For example: DESCRIPTION PROVIDED BY AUTHOR: The goal of my ... Author provided: The goal of my ... The goal of my ... END OF TRANSCR...
H: Regression: how to interpret different linear relations? I have three datasets, let's call them X and Y1 and Y2. A scatterplot is produced out of them, with Y1 and Y2 sharing them same X dataset (or support). My question: if the two regression lines are different in both slope and intercept, is there a way to evalu...
H: What are the best ways to tune multiple parameters? When building a model in Machine Learning, it's more than common to have several "parameters" (I'm thinking of real parameter like the step of gradient descent, or things like features) to tune. We validate these parameters on a validating set. My question is: wha...
H: Can k-means clustering get shells as clusters? Imagine you have $k$ classes. Every class $i$ has points which are follow a probability distribution, such that their distance to 0 is $i$ in mean, but this distance follows a normal distribution. The direction is uniformly distributed. So all classes are in shells aro...
H: Cluster Similar Images into Folders I wasn't sure where to ask this question so forgive me if the question seems out of place (and please guide me where to ask it !) I have an archive of 9GAG images and I want to Cluster them based on their content and their similarity... 9GAG images are mostly memes so it's natura...
H: Predicting future value with regression Model I have a set of predictor variables and another target variable . Now I am really confused on what method to use to forecast the target variable . For e.g my data set have customer profit(which is my target variable) and a set of predictor variable(balances of different...
H: Is Maxout the same as max pooling? I've recently read about maxout in slides of a lecture and in the paper. Is maxout the same as max pooling? AI: They are almost identical: The second key reason that maxout performs well is that it improves the bagging style training phase of dropout. Note that the arguments ...
H: Predicting app usage on mobile phone I'm currently building an app that strives to predict how the users uses different apps and give the user a suggestion based on which apps it think the user will currently use (a ranked list based on the user's current conditions). I've been collecting some data over the past we...
H: Decision tree vs. KNN In which cases is it better to use a Decision tree and other cases a KNN? Why use one of them in certain cases? And the other in different cases? (By looking at its functionality, not at the algorithm) Anyone have some explanations or references about this? AI: They serve different purposes. ...
H: Why do activation functions have to be monotonic? I am currently preparing for an exam on neural networks. In several protocols from former exams I read that the activation functions of neurons (in multilayer perceptrons) have to be monotonic. I understand that activation functions should be differentiable, have a ...
H: Pylearn2 vs TensorFlow I am about to dive into a long NN research project and wanted a push in the direction of Pylearn2 or TensorFlow? As of Dec 2015 has the community started to lean one direction or another? This link has given me concern about getting tied to TenserFlow. AI: You might want to take into conside...
H: Theano logistic regression example I am trying to understand some simple neural net case using theano. The deeplearning.net site gives the following simple code for implementing a logistic regression application to a simple case: import numpy import theano import theano.tensor as T rng = numpy.random N = 400 feats...
H: Calculating KL Divergence in Python I am rather new to this and can't say I have a complete understanding of the theoretical concepts behind this. I am trying to calculate the KL Divergence between several lists of points in Python. I am using this to try and do this. The problem that I'm running into is that the v...
H: How to draw a hyperplane using the weights calculated In the simple example where I have n input neurons, I can consider this to be a point in a n-dimensional space. If the output layer is just one neuron with value 0 or 1, if I get convergence, the neural net should define a hyperplane dividing the two classes of ...
H: Web services to mine the social web? Are there any web services that can be used to analyse data in social networks with respect to a specific research question (e.g. mentioning of certain products in social media discussions)? AI: Twitter's API is one of the best sources of social network data. You can extract off...
H: What is the appropriate evaluation metric for RandomForest with probability in R? In order to build a predict model with two categories (buy or not buy),I want to use RandomForest and predict with type='prob', so I can have a prob of someone buy or not buy. So, with this outcome I can clusterize and make groups, li...
H: Using predictive modelling for temperature data set I am absolutely new to this area of predictive modelling in data science. I am not able to understand how and what modelling techniques do we use? Does it depend on the data type? Does it depend on size of data? To be specific to the title, I have to predict missi...
H: Multi-class logistic regression I am trying to understand logistic regression for a multi-class example and I have the following code: import numpy import theano import theano.tensor as T rng = numpy.random num_classes = 3 #N = number of examples N = 100 #feats = number of input neurons feats = 784 #training rate ...
H: Early-Stopping for logistic regression. Theano I am trying to understand the code for the logistic regression on the official documentation, but I am struggling to understand the logic behind this code: # early-stopping parameters patience = 5000 # look as this many examples regardless patience_increase = 2 # ...
H: Hypertuning XGBoost parameters XGBoost have been doing a great job, when it comes to dealing with both categorical and continuous dependant variables. But, how do I select the optimized parameters for an XGBoost problem? This is how I applied the parameters for a recent Kaggle problem: param <- list( objective ...
H: Extremely dominant feature? I'm new to datascience. I was wondering how one should treat an extremely dominant feature. For example, one of the features is "on"/"off", and when it's "off", none of the other features matter and the output will just always be 0. So should I drop all rows where it's "off" in my train/...
H: Handling a feature with multiple categorical values for the same instance value I have data in the following form: table 1 id, feature1, predict 1, xyz,yes 2, abc, yes table2 id, feature2 1, class1 1, class2 1, class3 2, class2 I could perform a one many join and train on the resultant set- which is one way to go ...
H: How should I analyze this data from reddit (sample text included) I have downloaded some data to learn about machine learning and distributed computing. I used WinZip to uncompress a .bz2. Now I have text (opened in Notepad) which looks like this (this file is long, this is just a sample): {"parent_id":"t3_5yba...
H: Algorithm to construct similarity structure from hash lookup table I have constructed a lookup table using locality-sensitive hashing for comparing nearly similar documents/records. If two records (columns) have the same hash value in a row, they are considered to be similar. For example, the structure is R1 R2...
H: How to update weights in a neural network using gradient descent with mini-batches? [I've cross-posted it to cross.validated because I'm not sure where it fits best] How does gradient descent work for training a neural network if I choose mini-batch (i.e., sample a subset of the training set)? I have thought of thr...
H: How to analyse move kindness in python (Logistic regression, neural network, etc.)? With a team of researchers we were given the assignment to make a scale for the move kindness (how inviting a room or place is for exercise--e.g., a gym). In order to get objective results we were asked to make a measurement device....
H: Why in deep learning or another AI technique python is used rather than other languages? I want to know, why python? Instead of C#, Java, C\C++ and so on? AI: Short answers Tooling. Python has fantastic math, statistics, and linear algebra libraries. Less Code, Same Result. Python provides quick and simple ways of...
H: Handling categorical features in Factorization Machines algorithm - Feature Hashing vs. One-Hot encoding For solving a prediction problem I'm willing to use the Factorization Machines, a model that in addition to learning linear weights on features, learn a vector space for each feature to learn pairing interaction...