text stringlengths 83 79.5k |
|---|
H: Which approach for user classification on chat text (classifier, representation, features)?
I'm trying to train a classifier to classify text from a chat between 2 users so later on I can predict who of the two users is more likely to say X sentence/word. To get there I mined the text from the chat log and ended up... |
H: Does anyone could help me to understand what is the autoencoders?
Does anyone could help me to understand what the autoencoders means?
What we expect is that the outputs are equal to the inputs, then why we need to do that? It doesn't make any sense to me.
I find some interpretation that it learned how to reconst... |
H: Heatmap on a map in Python
Mode Analytics has a nice heatmap feature, but it is not conducive to comparing maps (only one per report).
What they do allow is data to be pulled easily into a wrapped python notebook. And then any image in python can easily be added to a report.
So my question is: how do I recreate a... |
H: Torch on Gentoo
Has anyone tried to install Torch on top of Gentoo Linux Distribution?
I'm very familiar with this distribution, but I'm totally new at torch. Googling a little, I found that Gentoo is not officially supported by torch (take a look at the install-deps script, line 142: https://github.com/torch/distr... |
H: Why would you split your train data to compute a value on half of the data to then fill the Nan values on the other half?
I was checking a kernel written in python from the Bosch kaggle competition (kaggle link to python kernel) and I came across with a weird (at least to me) way to fill Nan values.
The train data ... |
H: Association Rules - Data Mining - Train and Test approach?
Does it make sense to use the train, test, and validation model using the Association Rules Technique?
AI: Finding association rules is an unsupervised learning task (or exploratory task). You don't actually know which rules you want to find before you actu... |
H: Matrix based Visualization Meaning - Assocation Rules
I didn't found any good resource that explains me very well what type of information I can extract from a Matrix based Visualization like this:
I do't uderstand what RHS and LHS represents
Anyone can explain me the meaning of this chart?
Many thanks!
AI: An ass... |
H: Pandas - Get feature values which appear in two distinct dataframes
I have a Pandas DataFrame structured like this:
user_id movie_id rating
0 1 1193 5
1 2 1193 5
2 12 1193 4
3 15 1193 4
4 17 1193 5
5 18 1193 4
6 19 1... |
H: Checking for skewness in data
I have a data frame consisting of some continuous data features. I did a kde plot of the features using seaborn kdeplot functionality which gave me a plot as shown below :
How do I interpret this visualization in order to check for things like skew in the data points, etc.?
AI: IIUC y... |
H: SPARK RDD - Clustering - K-Means
Imagine that I've this dataset (just a sample)
A B C
1 23 1000
2 52 5000
3 12 500
4 10 450
I'm trying to assign each row to a clustering based on C value. Like this:
A B C CLUSTER
1 23 1000 2
2 52 5000 1
3 12 500 3
4 10 450 3
For tha... |
H: Is datawarehouse considered as datalake in big data environnment?
Suppose I have a datawarehouse (DWH) and now I would like to add many other bigdata sources of information most of them are not structured. I still keep the DWH with no architectural change. The only thing I do is to enrich the bigdata with the data ... |
H: Data set size versus data dimension, is there a rule of thumb?
I am trying to collect some data for ML, specifically for training a neural network model, and I don't know how big the data set is enough.
So is there a rule of thumb on how many data of dimension DIM should one collect for training a NN-Model ? For e... |
H: Spark MLLib - how to re-use TF-IDF model
I am using spark ml IDF estimator/model (TF-IDF) to convert text features into vectors before passing it to the classification algorithm.
Here's the process:
Datasets:
Full sample data (labeled) <br>
Training (labeled)<br>
Test (labeled)<br>
Unseen (non-labeled)<br>
This i... |
H: Contrasting logistic regression vs decision tree performance in specific example
I have a set of 10,000 integers, and another set of 100.
The integers in the first set are mapped to integers in the second set according to some rules (not mathematical rules, think of these values as codes for naming certain items, i... |
H: Help reducing a set of features
I am trying to do some clustering. I have a dataset that is very
sparse - with the majority of features only occurring in a single vector.
Here is a list of our features:
https://gist.github.com/scrooloose/5963725dc88e5d15d74dcae522bebf82
I am looking for any suggestions/hints/pointe... |
H: Difference between summation and integration
I understand calculus and maths but when i apply statistics and add up numbers they both look kinda same
Can anybody explain the difference in a little detail and simple manner please
AI: In most simple words-
Summation- Sum of a small numbers of large quantities.
Integ... |
H: Extract information from sentence
I'm creating a simple chatbot. I want to obtain the information from the user response. An example scenario:
Bot : Hi, what is your name?
User: My name is Edwin.
I wish to extract the name Edwin from the sentence. However, the user can response in different ways such as
User: Edw... |
H: After the training phase, is it better to run neural networks on a GPU or CPU?
My understanding is that GPUs are more efficient for running neural nets, but someone recently suggested to me that GPUs are only needed for the training phase. Once trained, it's actually more efficient to run them on CPUs.
Is this true... |
H: Use of Correlation Map in Machine Learning
I would like to know the use of correaltion map in machine leraning. For example, if there are 2 features with high correaltion, should either of the features be removed before appying the algorithm or it depends on every data set. Any explanation would be highly helpful. ... |
H: Difference between business and financial and data analyst
Can anyone please tell me whats the difference between
Business analyst
Financial analyst
Data analyst
And what should one need to learn in order to achieve either of these profile.
AI: Business Analyst
A business analyst is one who understands the specific... |
H: Network Plot - R - Modify Col
Having this R statement:
itemsets = apriori(data, parameter=list(support=0.05, confidence=0.5))
plot(itemsets, method="graph",
control=list(type="items"))
How can I change the colour of my plot? I try to insert "col" but don't allows me to do that because I'm getting the followi... |
H: Series prediction for any given time
I have a time series of data points. Then I am given a future timestamp and I have to predict the value for the data point. For simplicity, you can assume that the timestamp is bounded i.e. for e.g. query can be of at most 1 hr in the future.
This is different from tradition t... |
H: Plotting relationship between 2 data points where one data point is a boolean
I am working with the titanic survivors data set.
I have the data as a DataFrame and I can create 1D visualizations such as histograms, and also see the correlations by calling data.corr().
I would like to create a scatter plot to represe... |
H: Pros and Cons of Python and R for Data Science
So, let's start out by saying I am NOT asking which is better.
I like both of these languages for data science and I think this is a matter of and rather than or since there is no need to choose one of them. My general opinion is that R has more data science depth whil... |
H: Backpropagation derivation problem
I read a few tutorials on neural network backpropagation and decided to implement one from scratch. I tried to find this single error for the past few days I have in my code with no success.
I followed this tutorial in hopes of being able to implement a sine function approximator... |
H: Logistic regression with high cardinality categorical variable
I have a logistic regression model where I care about predictive power solely over comprehensibility. I'm interested in predicting win rates in a video game.
There are 133 characters. Each team picks 5 of them (no repeats). Each of these characters is a... |
H: Counting indexes in pandas
I feel like this is a rudimentary question but I'm very new to this and just haven't been able to crack it / find the answer.
Ultimately what I'm trying to do here is to count unique values on a certain column and then determine which of those unique values have more than one unique value... |
H: What is 'parameter convergence'?
I'm trying to teach myself data science, with my particular interest being decision trees. A few steps in, I've come across a term, 'parameter convergence' that I can't find a definition for (because, after all, I'm learning on my own and have no access to teachers or peers):
Howev... |
H: Median function in R
I tried
mtcars <- data.table( mtcars, keep.rownames=T)
mtcars[median(qsec),]
mtcars[order(qsec),]
This gives me 15th value though it should have given me the 16 value as the dataset has 32 values in it.
Please help me if I am doing something wrong... I know it's quite the basics
AI: I don't... |
H: How to do batch inner product in Tensorflow?
I have two tensor a:[batch_size, dim] b:[batch_size, dim].
I want to do inner product for every pair in the batch, generating c:[batch_size, 1], where c[i,0]=a[i,:].T*b[i,:]. How?
AI: There is no native .dot_product method. However, a dot product between two vectors is j... |
H: How to check if a data is in gaussian distribution in R or excel?
I know about the fitdist() function from the fitdistrplus package in R, however, I am not able to use it to predict a gaussian distribution. I can predict normal, logistic, weibull etc.
How can I use it for gaussian? are there any other ways to pred... |
H: What is the difference between dcast and recast in R?
I am working with a dataframe in R that is formatted like this sample:
Countries <- c('USA','USA','Australia','Australia')
Type <- c('a','b','a','b')
X2014 <- c(10, -20, 30, -40)
X2015 <- c(20, -40, 50, -10)
X2016 <- c(15, -10, 10, -100)
X2017 <- c(5, -5, 5, -10... |
H: Convolutional Neural Network: learning capacity and image coverage
I was looking through a CNN tutorial and towards the end they refer to learning capacity and image coverage during network learning diagnostics
What do those 2 terms mean in the context of a convolutional neural network?
AI: You can look at nolearn/... |
H: Did anybody ever use mean pooling and publish it?
I found a couple of sources which mention mean pooling for convolutional neural networks (CNNs) - including all lectures I had about CNNs so far - but I could not find any paper with at least 10 citations which uses mean pooling.
Do you know of a paper which uses me... |
H: Comparing SMOTE to down sampling the majority class in imbalanced binary classification
I have a binary classification task with imbalance between the two classes.
I want to compare SMOTE vs down sizing the majority class to the size of the minority class.
I trained the classifier with 3-fold validation using the t... |
H: Remove Outliers - Market Basket Analysis
I'm having some thoughts on whether I should remove the outliers. I'm trying to find the tags that are commonly used together. Imagine that I have the following dataset. The first column is the Tag_ID and the second column is the Number of People that used that Tag.
1 347... |
H: Practical use of oop in R
R supports a wide range of OOP designs like s3,s4,RC and others via packages,and it's a bit overwhelming to decide on which to use and a more basic question that I have is when and where do you use OOP while doing machine learning or data analytics ,can someone answer this from a data sc... |
H: Train/Test/Validation Set Splitting in Sklearn
How could I randomly split a data matrix and the corresponding label vector into a X_train, X_test, X_val, y_train, y_test, y_val with scikit-learn?
As far as I know, sklearn.model_selection.train_test_split is only capable of splitting into two not into three...
AI: Y... |
H: Autoregressive (AR) models constants - Time Series Analysis
I'm currently struggling with different Model like AR or MA.
If AR(1) is expressed as: $y_t = \beta + \beta_t \times y_{t-1} + \epsilon_t $
How do I know what the $\beta$ 's would be? What are the dependencies?
I think a simple example would help a lot.
AI... |
H: What's the best way to tune the regularization parameter in neural nets
I'm tuning the regularization parameter of a neural net (L2 regularization) using a grid. Starting with values 0.0005, 0.005, 0.05, 0.5, 5. Then if 0.005 brigs the best validation result, I continue using a grid like this: 0.0015, 0.0025, 0.003... |
H: Loss function for classifying when more than one output can be 1 at a time
My desired output is not 1-hot encoding, but
like a 10 D vector: [1, 0, 1, 0, 1, 0, 0, 1, 1, 1]
and the input is like the normal MNIST data set.
I want to use TensorFlow to build a model to learn this,
then which loss function should I choos... |
H: Efficiently Sending Two Series to a Function For Strings with an application to String Matching (Dice Coefficient)
I am using a Dice Coefficient based function to calculate the similarity of two strings:
def dice_coefficient(a,b):
try:
if not len(a) or not len(b): return 0.0
except:
return 0... |
H: How is dimensionality reduction achieved in Deep Belief Networks with Restricted Boltzmann Machines?
In neural networks and old classification methods, we usually construct an objective function to achieve dimensionality reduction. But Deep Belief Networks (DBN) with Restricted Boltzmann Machines (RBM) learn the da... |
H: How many vectors does paragraph vector generate for each paragraph?
For example,if I have a corpus with two paragraphs, does paragraph vector generate two vectors?Additionally, on Distributed Representations of Sentences and Documents (Q. Le, T. Mikolov) paper I do not understand why paragraph vectors are unique am... |
H: Why TensorFlow can't fit simple linear model if I am minimizing absolute mean error instead of the mean squared error?
In Introduction I have just changed
loss = tf.reduce_mean(tf.square(y - y_data))
to
loss = tf.reduce_mean(tf.abs(y - y_data))
and model is unable to learn the loss just became bigger with time. ... |
H: Recommendation/personalization algorithm conflict
I'm trying to build a recommendation engine for an e-commerce site. By using the common recommendation approach, I'm assuming that each product I recommend has the same value, so all I need to do is optimize the conversion rate probably using a common recommendation... |
H: Is there any other probability distribution model than gaussian for multivariate data
Whenever we talk about the probability distribution of data having more than one feature, we have only one option i-e multivariate normal distribution. Is there any other probability distribution model exist for multivariate data?... |
H: Validation during fitting in Keras
How does Keras' fit function calculate when validation set/validation split are NOT defined (I understand that the default values are None/0.0 respectively, so being not defined is practically default)? One always need a reference set to evaluate model performance...
AI: If you do... |
H: Methods / Algorithms for rank scales based on cumulative scoring
Say you have an organization that requires employees to participate in a Q&A site similar to StackOverflow - questions and answers are voted upon, selected answers get extra points, certain behaviors boost your score etc. What we need to do is assign... |
H: Replacing values in multiple columns of a data frame in R
for example consider this dataframe :
dam <- data.frame(name = letters[1:5],
re1 = factor(c("yes","no","yes","no","yes")),
re2 = factor(c("yes","no","yes","no","yes")),
re3 = factor(c("yes... |
H: What are interleaved layers of convolutions?
In the FaceNet paper, they describe the Zeiler&Fergus model like this:
[...] the
Zeiler&Fergus model which consists of multiple interleaved
layers of convolutions, [...]
What do they mean by interleaved? How does that compare to the inception layers?
Especially, as... |
H: How is the evaluation setup for YouTube faces of FaceNet?
The YouTube Faces database (YTF) consists of 3,425 videos of 1,595 different people. Given two videos, the task for YTF is to decide if they contain the same person or not. Having $n$ comparisons, the classifier might get $c \leq n$ right. Then the accuracy... |
H: How do CNNs use a model and find the object(s) desired?
Background: I'm studying CNN's outside of my undergraduate CS course on ML. I have a few questions related to CNNs.
1) When training a CNN, we desire tightly bounded/cropped images of the desired classes, correct? I.e. if we were trying to recognize dogs, we w... |
H: Using the trainbr function for classification in Matlab
I am training a neural network for classification using Matlab, and I don't understand if I can use the trainbr training function (Bayesian Regularization Backpropagation). It uses the MSE performance measure, but I want to use the crossentropy. If I set cross... |
H: How does the Nearest Centroid method work?
I have read this Wikipedia article.
But, the idea is still very fuzzy to me.
Suppose, k=5.
Then, we have,
$X_5 = \{A, B, C, D, E\}$
$Y_2 = \{Triangle, Square\}$
$R_5 = \{9, 8, 5, 1, 4 \}$ (just assumed)
Now, $\mu_{Triangle} = \frac{5}{2} = 2.50$
and, $\mu_{Square} = \f... |
H: Can overfitting occur even with validation loss still dropping?
I have a convolutional + LSTM model in Keras, similar to this (ref 1), that I am using for a Kaggle contest. Architecture is shown below. I have trained it on my labeled set of 11000 samples (two classes, initial prevalence is ~9:1, so I upsampled the ... |
H: Big data analytics references
I'm looking for a good introductory book or course to big data analytics.
For the practical part, I'm particularly interested into using big data tools in R.
I would prefer a book, but other references are welcome.
Thanks!
AI: I tried to explore some of the best available resources, w... |
H: Predefined Neural Networks instead of fine tuning?
I usually try to form my ANNs with classic fine-tuning approach but I recently learned that there are different "predefined" networks specially for certain tasks. Is there a good summary about these? Are they really perform better than home-made ones?
AI: It depend... |
H: Visualizing results of a classification problem, excluding confusion matrices?
A classification system I built is going to go into production soon (it'll be part of a larger dashboard), and I'm looking for ways to better visualize and convey to business folks the results of a classification.
Basically, given "old" ... |
H: Image feature extraction Python skimage blob_dog
I am trying to extract features from images using:
def process_image(image_fp):
image_ = imread(image_fp)
image_ = resize(image_, (300, 200,3))
image=equalize_hist(rgb2gray(image_))
edges = skimage.feature.blob_dog(image)
return edges.reshape(edge... |
H: Choice of replacing missing values based on the data distribution
I am building a classification model based on a relatively small dataset. I have some missing values on the different attributes that I have. I cannot afford deleting any of the record that has missing values so I want to replace them.
I made some g... |
H: Which recommender system approach allows for inclusion of user profile?
I wanted to enhance a recommendation engine with information relying not only on past purchases or ratings but also on behavioral and demographical variables like sex, age, location, service usage frequency or hours. This information may be spa... |
H: How to equalize the pairwise affinity perplexities when implementing t-SNE?
I'm trying to implement the t-SNE algorithm:
I found that to compute the pairwise affinities, I have to follow this:
My problem is computing $\sigma_i$. In the Wikipedia I found:
The bandwidth of the Gaussian kernels $\sigma_{i}$,
is s... |
H: How does Xgboost learn what are the inputs for missing values?
So from Algorithm 3 of https://arxiv.org/pdf/1603.02754v3.pdf, it says that an optimum default direction is determined and the missing values will go in that direction. However, or perhaps I have misunderstood/missed the explanation from the article, it... |
H: Convolutional autoencoders not learning
I'm trying to implement convolutional autoencoders in tensorflow, on the mnist dataset.
The problem is that the autoencoder does not seem to learn properly: it will always learn to reproduce the 0 shape, but no other shapes, in fact I usually get an average loss of about 0.09... |
H: Dataframe request with groupBy
I'm a beginner in Spark and I want to calculate the average of number per name.
I have a JSON file with this information
df = spark.read.json("myjson.json")
df.select(avg(df["number"]), df["name"]).groupBy("name").show()
But I'm doing it wrong..
How can I solve my problem?
Thanks a ... |
H: Topics to cover for software developer interested in data analytics
First of all I don't know if this is the appropriate place to post this question. If it's not, I apologize in advance. It seems like the most relevant Stack Exchange sub.
A little about myself:
I'm a software developer and have been working in the ... |
H: Spark Mllib - FPG-Growth - Machine Learning
Is the FPG-Growth an Machine Learning algorithm? Because I'm looking at this code:
import org.apache.spark.mllib.fpm.FPGrowth
import org.apache.spark.rdd.RDD
val data = sc.textFile("data/mllib/sample_fpgrowth.txt")
val transactions: RDD[Array[String]] = data.map(s => s.... |
H: Methods to reduce dimensionality within a feature?
Suppose that I am interested in predicting an outcome (say, the arrival delay [in seconds] of a flight) based upon a set of features.
One of these features is a nominal variable - carrier - that specifies the airline carrier of the flight. This feature has 16 diff... |
H: Variance in cross validation score / model selection
Between cross-validation runs of a xgboost classification model, I gather different validation scores. This is normal, the Train/validation split and model state are different each time.
flds = self.gsk.Splits(X, cv_folds=cv_folds)
cvresult = xgb.cv(xgb_param, xg... |
H: PCA on matrix with large M and N
Based on this answer, we know that we can perform build covariance matrix incrementally when there are too many observations, whereas we can perform randomised SVD when there are too many variables.
The answer provide are clear and helpful. However, what if we have a large amount o... |
H: What is the reward function in the 10 armed test bed?
The Sutton & Barto book on reinforcement learning mentions the 10 armed test bed in chapter 2, Bandit Problems:
To roughly assess the relative effectiveness of the greedy and
ε-greedy methods, we compared them numerically on a suite of test
problems. This w... |
H: What are some good error metrics for multi-label (not mutli-class) problem in industry?
What are some good error metrics for multi-label (not mutli-class) problem in industry?
http://scikit-learn.org/dev/modules/multiclass.html
AI: A common example is the Jaccard similarity coefficient:
$J(Y, P) = \frac{|Y~\cap~P|}... |
H: What is a better approach for cross-validation with time-related predictors
I was a given a data set with different predictors about a store and the idea is to forecast the number of daily shoppers. The predictors are the weekday, time of the day (morning, afternoon, evening), week number, month, weather (humidity,... |
H: Check Accuracy of Model Provided by Consultant
My company has recently engaged a consultant firm to develop a predictive model to detect defective works.
I understand that there are many ways to validate the model, for example, using k-fold cross-validation and I believe that the consultant firm will carry out the ... |
H: What is stored in heap structure in the following example?
I am planning to use heap structure to find the minimum distance between a set of 2D points and form a cluster.. and after to spend a couple of hours surfing on the internet, I have not still gotten a clearly example.
Imagine you have a set of 2d points (x1... |
H: SVD for recommendation engine
I'm trying to build a toy recommendation engine to wrap my mind around Singular Value Decomposition (SVD). I've read enough content to understand the motivations and intuition behind the actual decomposition of the matrix A (a user x movie matrix).
I need to know more about what goes o... |
H: roc_auc score GridSearch
I am experimenting with xgboost.
I ran GridSearchCV with score='roc_auc' on xgboost. The best classificator scored ~0.935 (this is what I read from GS output). But now when I run best classificator on the same data:
roc_auc_score(Y, clf_best_xgb.predict(X))
it gives me score ~0.878
Could ... |
H: Sigmoid vs Relu function in Convnets
The question is simple: is there any advantage in using sigmoid function in a convolutional neural network? Because every website that talks about CNN uses Relu function.
AI: The reason that sigmoid functions are being replaced by rectified linear units, is because of the proper... |
H: K-Means Algorithm - Feature Selection
Suppose I've this dataset:
Employee_ID Store_ID Company_ID Stock_ID Product_Value
1 1 1 2 3.7
4 1 4 2 8
...
Where:
Employee_ID: Is the unique number for a empl... |
H: Recommendation System to integrate with an android app
I need to build a recommendation system that takes certain parameters as input, computes a score and order suggestions to users based on this score. Well this is what I need to do loosely speaking. I am new to the scene of data science and haven't come across a... |
H: Why is this Binning by Median code wrong?
I was working on Binning by Mean, Median and Boundary in R.
# R CODE
a=c(20.5, 52.5, 62.6, 72.4, 104.8, 63.9, 35.3, 83.9, 37.4, 71.6, 74.6, 44.5, 66.6, 56.1, 45.3, 37.2)
a=sort(a)
binsize=4
median(a[1:4])
# BINS ARE
for(i in 1:length(a))
{
if(i%%binsize==0)
{
print(... |
H: How to handle a zero factor in Naive Bayes Classifier calculation?
If I have a training data set and I train a Naive Bayes Classifier on it and I have an attribute value which has probability zero. How do I handle this if I later want to predict the classification on new data? The problem is, if there is a zero in ... |
H: Example of Logistic Regression using a proportion as the dependent variable?
I am trying to run a logistic regression on a data set where my dependent variable is a proportion of a binary variable, rather than the binary variable itself. I have seen a ton of documentation that says this is possible, but I am havi... |
H: How do you evaluate ML model already deployed in production?
so to be more clear lets consider the problem of loan default prediction. Let's say I have trained and tested off-line multiple classifiers and ensembled them. Then I gave this model to production.
But because people change, data and many other factors ch... |
H: Understanding autoencoder loss function
I've never understood how to calculate an autoencoder loss function because the prediction has many dimensions, and I always thought that a loss function had to output a single number / scalar estimate for a given record. However, on GitHub I recently came across a repository... |
H: Deep Learning Project to Predict Stock Prices
So I have a background in computer programming and a little in machine learning in general. What I would like to do is create a fun project in A.I. with deep learning.
I have a dataset that has a whole bunch of stock prices at a certain date, with a bunch of features ... |
H: Filtering outliers in Apache Spark based on calculations of previous values
I'm processing geospatial data using Spark 2.0 Dataframes with the following schema:
root
|-- date: timestamp (nullable = true)
|-- lat: double (nullable = true)
|-- lon: double (nullable = true)
|-- accuracy: double (nullable = true)
... |
H: Can you interpret probabilistically the output of a Support Vector Machine?
I am trying to build a binary classification system using different classification algorithms like random forests, support vector machines, AdaBoost. I want to use the output of these classifiers to visualize a score. For example, when usin... |
H: Which machine learning algorithm should I apply for differentiate question difficulty level with users' result
Here's the scenario, There's a database with thousands of single-option questions for testing a specific skills, and a large number of users (either professional or amateur in this skill), each of which an... |
H: Intuition Behind Restricted Boltzmann Machine (RBM)
I went through Geoff Hinton's Neural Networks course on Coursera and also through introduction to restricted boltzmann machines, still I didn't understand the intuition behind RBMs.
Why do we need to compute energy in this machine? And what is the use of the prob... |
H: How to find the filename associated with a prediction in Keras?
My question is really simple, how to find the filename associated with a prediction in Keras? That is, if I have a set of 100 test samples named and I get a numpy array which contains the estimated class probabilities, how do I map the filenames to th... |
H: Train/Test Split after performing SMOTE
I am dealing with a highly unbalanced dataset so I used SMOTE to resample it.
After SMOTE resampling, I split the resampled dataset into training/test sets using the training set to build a model and the test set to evaluate it.
However, I am worried that some data points in... |
H: Failure tolerant factor coding
There are a lot of ml-algorithms which cannot directly deal with categorical variables.
A very common solution is to apply binary (dummy-) coding to still properly handle the categorical nature of the data.
Very often e.g. in sk-learn or apache-spark the actual dummy-coder can only h... |
H: # of iterations in Restricted Boltzmann Machine (RBM)
I have a training set, I provide it (consider a data from training set) to the visible layer. Then the normal process is followed, i.e. Positive Phase-> Negative Phase-> Reconstruction of weights, bias units take place. Does it end here or should I have to itera... |
H: Outliers Approach
Having a schema which the majority of the values are IDs. Like this example (this isn't my real data):
ID SCHOOL_ID CLASSE_ID STUDENT_ID GRADE
1 1 1 1 17
2 1 1 2 10
3 1 1 3 4
4 ... |
H: How to add a new category to a deep learning model?
Say I have done transfer learning on a pre-trained network to recognize 10 objects. How can I add a $11^{th}$ item that the network can classify without losing all the 10 categories I already trained and the information from the original pre-trained model? A frien... |
H: How hidden layer is made binary in Restricted Boltzmann Machine (RBM)?
In RBM, in the positive phase for updating the hidden layer(which should also be binary), [Acually consider a node of h1 ∈ H(hidden layer vector)] to make h1 a binary number we compute the probability of turning on a hidden unit by operating act... |
H: Feature engineering using XGBoost
I am participating in a kaggle competition. I am planning to use the XGBoost package (in R). I read the XGBoost documentation and understood the basics.
Can someone explain how is feature engineering done using XGBoost?
An example for explanation would be of great help.
AI: It turn... |
H: How to test People similarity measure?
I am doing a project on finding famous people who are similar to each other.
For this, I am extracting a bunch of features and applying a distance function on them to evaluate who is closer to whom.
Is there a way to test this out quantitatively? Take the example of actors fo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.