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H: How to do imbalanced classification in deep learning (tensorflow, RNN)?
I am trying to do binary classification of News Articles (Sports/Non-Sports) using recurrent neural net in tensorflow. The training data is highly skewed [Sports:Non-Sports::1:9].
I am using cross-entropy as my cost function, which treats both ... |
H: How to extract most occuring words based on month & what tool to use?
Hi guys I'm very new to data science,
I have intermediate background on programming and have used Pentaho Data Integration tool once for DB migration & data cleansing.
Let's say I have this kind of data:
item_details, timestamp
Wooden chairs, 01... |
H: Installing Orange Package with older Python Version?
I am trying to install an Add-on package from GitHub that contains prototype widgets for Orange Data Mining. I am trying to install it from the GitHub page found here.
I am using the following Terminal code to install this:
git clone http://github.com/biolab/oran... |
H: Feature reduction convenience
In the field of machine learning, I'm wondering about the interest of applying feature selection techniques.
I mean, I often read articles or lectures speaking about how to reduce the number of feature (dimensionality reduction, PCA), how to select the best features (feature selection ... |
H: Is there a way to measure correlation between two similar datasets?
Let's say that I have two similar datasets with the same size of elements, for example 3D points :
Dataset A : { (1,2,3), (2,3,4), (4,2,1) }
Dataset B : { (2,1,3), (2,4,6), (8,2,3) }
And the question is that is there a way to measure the correla... |
H: Convolutional neural network fast fourier transform
I've read that some convolution implementations use FFT to calculate the output feature/activation maps and I'm wondering how they're related. I'm familiar with applying CNNs, and (mildly) familiar with the use of FFT in signal processing, but I'm not sure how the... |
H: Multiple testing of unbalanced data by R
I have a general question of unbalanced data. I'm performing a T test on Group A and Group B. Group A has 20 data while Group B has 500. I set unequal variance (Welch) for the adjustment and the P-value is 0.01. Can I conclude that there is significance?
I have another idea... |
H: XGBRegressor vs. xgboost.train huge speed difference?
If I train my model using the following code:
import xgboost as xg
params = {'max_depth':3,
'min_child_weight':10,
'learning_rate':0.3,
'subsample':0.5,
'colsample_bytree':0.6,
'obj':'reg:linear',
'n_estimators':1000,
'eta':0.3}
features = df[feature_columns]
t... |
H: How relevant is Self Organizing Maps in today's science?
Self-Organizing Maps is a pretty smart yet fast & simple method to cluster data. But Self-Organizing maps were developed in 1990 and a lot of robust and powerful clustering method using dimensionality reduction methods have been developed since then. What are... |
H: Why use convolutional NNs for a visual inspection task over classic CV template matching?
I had an interesting discussion come up based on a project we were working on: why use a CNN visual inspection system over a template matching algorithm?
Background: I had shown a demo of a simple CNN vision system (webcam + l... |
H: Forecasting non-negative sparse time-series data
I have a time-series dataset (daily frequency) representing the sales of a product to a customer over time. The sales is represented as the following:
$$[0, 0, 0, 0, 24, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 17, 0, 0, 0, 0, 9, 0, ...]$$
in which each number represents ... |
H: Order SparseVectors by the closest distance to given SparseVector
I have a Spark dataset containing a column of SparseVector types. Additionally, I have another SparseVector $X$ which is not a part of the dataset. I want to order my dataset according to the closest distance (or similarity) relative to $X$.
Can anyo... |
H: Gradient Boosting Tree: "the more variable the better"?
From the tutorial of the XGBoost, I think when each tree grows, all the variables are scanned to be selected to split nodes, and the one with the maximum gain split will be chosen. So my question is that what if I add some noise variables into the data set, wo... |
H: Cross-validation of a cross-validated stacking ensemble?
let me begin by saying that I understand how to build a stacked ensemble by using cross-validation to generate out-of-fold predictions for the base learners to generate meta-features. My question is about the methodology when cross-validating the entire stack... |
H: Different available packages in TensorFlow virtualenv?
I have installed TensorFlow on Linux (Anaconda) by following the documentation which states that one should create and activate a virtual environment tensorflow. So far, so good (albeit it is not entirely clear why is this virtual environment is necessary when ... |
H: Installing Prototype Widgets in Orange running on Mac
I am having trouble downloading some add-ons for the Orange data mining software that are not available through the normal add-ons menu. To do this, I am attempting to install a particular set of add-ons from the GitHub page here.
I am very novice when it comes ... |
H: Has anyone tried to use the hierarchy of ImageNet?
The classes of ImagNet have a hierarchy. Did anybody try to build a hierarchy of classifiers to use this fact?
Searching for "multistage classification" leads to different results.
AI: Yes, multiple papers have used this. I've heard of multiple ways to exploit this... |
H: Using Generative Adversarial Networks for a generation of image layer
Has anybody seen any application that would use GAN that would take input image and would output image of the same size, that could be used as a layer for the first image. The layer would contain in eg. point of interest in the input image. Would... |
H: Problem designing CNN network
I seem to have a problem modelling my CNN network.
I want to extract from features vector from different sized images.
Whats consistent with the images is the y-axis, and the color dimension, but the x-axis is not constant.
Depending on the length of the x-axis will the length of th... |
H: Retrain final layer of Inception model
I'm trying to retrain Inception model final layer for a binary classification.
My training image set contain 2000 images in class 1 and more than 6000 images in class 2.
Will this huge difference in number of images of each class in training set affect my classification?
AI: T... |
H: Which graph will be appropriate for the visualization task?
I have some terminal charging values for US and CHINA
comes in a pandas DataFrame like the following,
value country
0 550.0 USA
1 820.0 CHINA
2 835.0 CHINA
3 600.0 USA
4 775.0 ... |
H: How to test accuracy of an unsupervised clustering model output?
I am trying to test how well my unsupervised K-Means clustering properly clusters my data. I have an unsupervised K-Means clustering model output (as shown in the first photo below) and then I clustered my data using the actual classifications.
The ... |
H: Pandas v. SFrame in learning data science
I'm taking a machine learning course that introduces the related assignments as such that a student may use either Pandas or SFrame in solving them. As a beginner, it's hard for me to assess which approach would be more beneficial for me in the long run. Hence the question;... |
H: Designing CNN that does one column convolution across the x-axis
I am currently working on designing a certain number of CNN for extracting features from images.
The images are spectogram, and each have a shape being (276,x,3).
X is here the number of column, which incidently also the length of the feature vector ... |
H: Data Scientist Consulting Interview Guide
Does anyone have any books or blogs that specifically sheds light on questions to ask your organization (from a consulting POV) as a data scientist? I am a new data scientist, which I have a background in consulting and predictive analytics.
There are several good reads su... |
H: Which algorithm can i use for predicting length of stay in coming year based on historical claims data?
I have two years historical health claims data of one thousand members. Based on this two years data, I have to predict length of stay in hospital in 3rd year for all members. here is the data sample.
Year MembID... |
H: Selecting dataset splitting strategy
I found this very informative figure, on how to split the dataset depending on how much data (or how many observations to be more precise) you have.
My question is, since "less data" is very subjective, is there a statistical test you can perform or even a rule of thumb on whi... |
H: What is a batch in machine learning?
Karpathy's' LSTM batch network LSTM batch network operates with batches
def checkSequentialMatchesBatch():
""" check LSTM I/O forward/backward interactions """
n,b,d = (5, 3, 4) # sequence length, batch size, hidden size
input_size = 10
WLSTM = LSTM.init(input_si... |
H: How does one deploy a model, after building it in Python or Matlab?
I have been playing around with a lot of different machine learning models (clustering, neural nets, etc...), but I am sort of stuck on understanding what happens after you finish building the model in Python or Matlab.
For example, let's say that ... |
H: How to deal with string labels in multi-class classification with keras?
I am newbie on machine learning and keras and now working a multi-class image classification problem using keras. The input is tagged image. After some pre-processing, the training data is represented in Python list as:
[["dog", "path/to/dog/i... |
H: Alternative methods for improved clustering separation?
I have the following labeled cluster, which is what an ideal clustering algorithm would generate:
Now, I have applied a basic K-Means clustering algorithm to the data, and the outcome is as follows:
I recognize that this is a tough problem to properly cluste... |
H: Fine-tuning a model from an existing checkpoint with TensorFlow-Slim
I'm trying to retrain the final layer of a pretrained model with a new image dataset using TensorFlow-Slim.
Lets say I want to fine-tuning inception-v3 on flowers dataset. Inception_v3 was trained on ImageNet with 1000 class labels, but the flowe... |
H: Extracting Features Using TensorFlow CNN
I'm trying to extract features of set of images. I'm using CNN from this site.
Can anyone please tell me how to do feature extraction of images using CNN? I looked for various places. But nowhere it's clearly mention the feature extraction part.
AI: Actually, after you've co... |
H: Kernel trick explanation
In support vector machines, I understand it would be computationally prohibitive to calculate a basis function at every point in the data set. However, it is possible to find this optimal solution due to the so-called kernel trick.
Other answers to this question use advanced math and statis... |
H: Wrong output multiple linear regression statsmodels
I recently moved to python for data analysis and apparently I am stuck on the basics. I am trying to regress the parameters of the following expression: z=20+x+3*y+noise, and I get the right intercept but the x and y parameters are clearly wrong. What am I doing m... |
H: Which Amazon EC2 instance for Deep Learning tasks?
I have discovered that Amazon has a dedicated Deep Learning AMI with TensorFlow, Keras etc. preinstalled (not to mention other prebuilt custom AMIs). I tried out this with a typical job on several GPU-based instances to see the performances. There are five such in ... |
H: make seaborn heatmap bigger
I create a corr() df out of an original df. The corr() df came out 70 X 70 and it is impossible to visualize the heatmap... sns.heatmap(df). If I try to display the corr = df.corr(), the table doesn't fit the screen and I can see all the correlations. Is it a way to either print the enti... |
H: CNN for classification giving extreme result probabilities
I'm having issues with my CNN, using Keras with Theano backend.
Basically, I need to classify 340x340 grayscale images into 6 categories. The problem is my CNN gives too "hard" probabilities, for instance it will rarely give predictions with some uncertaint... |
H: Application of Machine learning or Neural Networks for automatic Time table scheduling
I've been trying to come up with an intelligent solution to build a Time table scheduling application with the use of Machine learning or Neural networks. What would be the algorithm or approach to build such application. I'm pla... |
H: Interpretation of an SVD for recommender systems
The idea is to motivate the SVD for use in a recommender system.
Consider a matrix $A\in \mathbb{R}^{f\times u}$ where $A_{ij}$ caputures how user $j$ rates film $i$ (on a scale from 1-10, some entries may be missing).
Considering matrices $K=AA^T$, $L = A^TA$ what ... |
H: Adding more features in SVC leading to worse performance, even w/ regularization
I have a relatively small dataset of 30 samples with binary labels (16 positive and 14 negative). I also have five continuous features for each these samples. I'm trying to use the support-vector classifier (SVC) for this task. I te... |
H: Run Apriori algorithm in python 2.7
I have a DataFrame in python by using pandas which has 3 columns and 80.000.000 rows.
The Columns are: {event_id,device_id,category}.[]
each device has many events and each event can have more than one category.
I want to run Apriori algorithm to find out which categories seem to... |
H: Using TensorFlow with Intel GPU
Is there any way now to use TensorFlow with Intel GPUs? If yes, please point me in the right direction.
If not, please let me know which framework, if any, (Keras, Theano, etc) can I use for my Intel Corporation Xeon E3-1200 v3/4th Gen Core Processor Integrated Graphics Controller.
A... |
H: Why are variables of train and test data defined using the capital letter (in Python)?
I hope this question is the most suitable in this site...
In Python, usually the class name is defined using the capital letter as its first character, for example
class Vehicle:
...
However, in machine learning field, often... |
H: HTML Words Remover?
Does anyone know if there is functionality similar to StopWordsRemover but intended to clean out HTML syntax? e.g. get the text without any html tags after transformation.
AI: Wrote simple class - if someone will be interested:
import org.apache.spark.ml.Transformer;
import org.apache.spark.ml.p... |
H: GANs to augment training data
I have been reading about Generative Adversarial Networks (GANs) and was wondering if it would make sense to train a generator function only to use it for creating more training data.
In a scenario where I don't have enough training data to build a robust classifier, can I use this lim... |
H: TensorFlow with Phonegap
I'm new into the ML Scene and I want to create a phonegap app involving Tensorflow but I'm unsure where to start or if this is even possible. Can anyone give me a hand (Probably by linking me to some resources)? My app will just use tensor flow image recognition (probably pre-trained).
Than... |
H: EEG data layout for RNN
How should one structure an input data matrix (containing EEG data) for an RNN?
Normally, RNNs are presented as language models where you have a one hot vector indicating the presence of a word. So if you input was the sentence "hello how are you", you would have 4 one hot vectors (I think):... |
H: Is ML a good solution for identifying what the user wants to do from a sentence?
I am learning machine learning and I'm trying to implement a solution for a real problem: predict from a human sentence what programming function he/she is trying to do.
I have a series of programming functions related with a series of... |
H: Is Overfitting a problem in Unsupervised learning?
I come to this question as I read the use of PCA to reduce overfitting is a bad practice. That is because PCA does not consider labels/output classes and so Regularization is always preferred.
That seems purely valid in Supervised Learning.
What about the case fo... |
H: SWF - Incremental mining
I am new to this data mining. Can anyone please help me with an example for Sliding Window Filtering algorithm(SWF) for incremental mining?
AI: There are pseudo-codes in this paper, Section 3.1 shows an example of incremental mining by this algorithm. However I can't find any projects or wo... |
H: Finding the perfect algorithm for realtime optimizing of content
I am looking for an algorithm that allows me the following:
I have a webpage and I want to randomly show one "content" from a list of contents on that webpage depending on who (visitor) sees the webpage. I know my visitors' demographic features like a... |
H: How do I represent a hidden markov model in data structure?
My task involves a POS Tagging using HMM. I am given a training data set (word/tag). I have to write a file with transition probabilities and emission probabilities. I am currently using a nested dictionary of the form {State1: {State2: count, State3 :coun... |
H: Which type of regression has the best predictive power for extrapolating for smaller values?
I have a data set which deals with response variable in the order of 10-20. The scatter plot for such a regression appears linear, but the problem being when I predict for test cases using values very small compared to the ... |
H: Correct number of biases in CNN
What is the correct number of biases in a simple convolutional layer? The question is well enough discussed, but I'm still not quite sure about that.
Say, we have (3, 32, 32)-image and apply a (32, 5, 5)-filter just like in Question about bias in Convolutional Networks
Total number o... |
H: Best way to fix the size of a sentence [Sentiment Analysis]
I am working on a project that is about Natural Language Processing. However I am stuck at the point which is I have a ANN that has fixed size of input neurons.
I am trying to do sentiment analysis with using Imdb movie review set. To able to do that, fir... |
H: Retrieving column names in R
I am trying to retrieve the column names of the data set model$data using the following formula:
sample(colnames(model$data),1)
When I run it I receive the following error message:
Error in sample.int(length(x), size, replace, prob) :
invalid first argument
Appreciate any help!
str... |
H: Pandas categorical variables encoding for regression (one-hot encoding vs dummy encoding)
Pandas has a method called get_dummies() that creates a dummy encoding of a categorical variable. Scikit-learn also has a OneHotEncoder that needs to be used along with a LabelEncoder. What are the pros/cons of using each of t... |
H: How should I expose data from my app for data scientists?
I'm the product manager for an online app. I'm currently researching a new feature where our users will be able to access "all their raw application data". This data is likely to be used by data scientists, it's also likely to be loaded into BI tools. The... |
H: How to treat outliers in a time series dataset?
I've read the following article about how to treat outliers in a dataset: http://napitupulu-jon.appspot.com/posts/outliers-ud120.html
Basically, he removes all the y which has a huge difference with the majority:
def outlierCleaner(predictions, ages, net_worths):
... |
H: Does it make sense to train a CNN as an autoencoder?
I work with analyzing EEG data, which will eventually need to be classified. However, obtaining labels for the recordings is somewhat expensive, which has led me to consider unsupervised approaches, to better utilize our quite large amounts of unlabeled data.
Th... |
H: How to fill missing value based on other columns in Pandas dataframe?
Suppose I have a 5*3 data frame in which third column contains missing value
1 2 3
4 5 NaN
7 8 9
3 2 NaN
5 6 NaN
I hope to generate value for missing value based rule that first product second column
1 2 3
4 5 20 <--4*5
7 8 9
3 2 6 <-- 3*2
5 6 ... |
H: How can I handle missing categorical data that has significance?
I have a data set that is highly categorical and has a lot of missing values. For instance:
i | A_foo | A_bar | A_baz | outcome
--+-------+-------+-------+--------
0 | nan | nan | nan | 1
1 | 0 | 1 | 0 | 1
2 | nan | nan | na... |
H: How to improve an existing machine learning classifier in python?
I have a big dataset (1million x 50) to which I want to predict a particular class. I have thought of segregating the dataset in batches of 20k. And then train a classifier (lets say random forest or a basic SVM). How do I then improve that classifie... |
H: Is there an R package for Locally Interpretable Model Agnostic Explanations?
One of the researchers, Marco Ribeiro, who developed this method of explaining how black box models make their decisions has developed a Python implementation of the algorithm available through Github, but has anyone developed a R package?... |
H: Generalization Error Definition
I was reading about PAC framework and faced the definition of Generalization Error. The book defined it as:
Given a hypothesis h ∈ H, a target concept c ∈ C, and an underlying distribution
D, the generalization error or risk of h is defined by
The generalization error of a h... |
H: Forecasting time series: Method Selection
Im new to forecasting time series and Im looking for some advice on selecting the best method based on the analaysis of the graph.
I have the following data and based on the little knowledge I have, Im assuming it is a stationary time series because of the shape of the dat... |
H: In multiple linear regression why is it best to use an $F$-statistic when evaluating predictors?
I am currently going through Hastie and Tibshirani's 'Introduction to Statistical Learning' textbook and I have come across something I don't understand on page 77. I have two questions.
The author states that if we had... |
H: RandomForestClassifier : binary classification scores
I am using sklearn's RandomForestClassifier to build a binary prediction model. As expected, I am getting an array of predictions, consisting of 0's and 1's. However I was wondering if it is possible for me to get a value between 0 and 1 along with the predictio... |
H: Sales prediction of an Item
So, I've been trying to implement my first algorithm to predict the (sales/month) of a single product, I've been using linear regression since that was what were recommended to me. I'm using data from the past 42 months, being the first 34 months as training set, and the remaining 8 as ... |
H: What is Ground Truth
In the context of Machine Learning, I have seen the term Ground Truth used a lot. I have searched a lot and found the following definition in Wikipedia:
In machine learning, the term "ground truth" refers to the accuracy of the training set's classification for supervised learning techniques. ... |
H: Can generic data sets be suitable for specific sentiment analysis
I have used the stanford movie review dataset for creating a experimentation of sentiment analysis.
Managed to create a basic application on top of Spark using the Naive bayes classification algorithm.
Steps that I did for pre-processing from the spa... |
H: Reward dependent on (state, action) versus (state, action, successor state)
I am studying reinforcement learning and I am working methodically through Sutton and Barto's book plus David Silver's lectures.
I have noticed a minor difference in how the Markov Decision Processes (MDPs) are defined in those two sources,... |
H: Estimate the normal distribution of the mean of a normal distribution given a set of samples?
Let's say there is a distribution, call it D, for which I don't know details (i.e. mean and variance) but can assume that it's a normal distribution. I now have N samples from D. I cannot take more samples because it's too... |
H: How to shift rows values as columns in pandas?
Input: I have csv file like below as input....
ID, Year,Specialty,AgeRange,PlaceSvc,Count, Group
101,2009,Internal, 20-29, Office, 0, PRGNCY
101,2010,Emergency, 20-29, Urgent Care,0, GIOBSENT
101,2011,Internal, 20-29, Office, 0, GYNEC1
102,2010,Other, ... |
H: Can't reproduce results from GridSearchCV?
I am trying to find optimized n_neighbors value for KnearestClassifier using GridSearchCV. I am able to get optimized parameters but when I enter those in my classifier results don't match with GridSearchCVs best results.
clf = KNeighborsClassifier(n_neighbors=15, weights=... |
H: Missing data imputation with KNN
-1
down vote
favorite
I have a dataset including missing data for most of the variables. Assume the dataset is as follows:
Obs. var1 var2 var3 var4 var5 var6
1 x11 x12 x13 x14 Nan Nan
2 x21 x22 x23 Nan x25 x26
3 x31 x32 x33 x34 x35 x36... |
H: State of the art for Object detection/image recognition
I was asked to verify the feasibility for solving a particular problem: recognizing for a fashion brand the model of its products.
I have little experience with image recognition in general, I always used Google Vision Api or some pre trained nets from Google... |
H: Is it scientifically correct to derive conclusions unrelated to hypothesis from A/B test data
Consider a software A/B test with the hypothesis that "the addition of feature F is predicted to increase metric X".
At the end of the test, the data doesn't show any significant change in X, but it does show a significant... |
H: python - What is the format of the WAV file for a Text to Speech Neural Network?
I am creating a Text to Speech system for a phonetic language called "Kannada" and I plan to train it with a Neural Network. The input is a word/phrase while the output is the corresponding audio.
While implementing the Network, I was ... |
H: Ordered elements of feature vectors for autoencoders?
Here is a newbie question; when one trains an autoencoder or a variational autoencoder, does the order of the objects in the training vector $x$ matter?
Suppose I take an MNIST image image $(28\times28)$ and turn it into a feature vector of size $x \in \mathbb{R... |
H: Predict the date an item will be sold using machine learning
I would like to predict the date a item will be sold using features such as:
Product ID Price Days_since_first_post Last_repost Type First_Post_Date Sold_Date
How would machine learning principles be used in ... |
H: sentence classification with RNN-LSTM - output layer
i have read a few blogs and papers on the IMDB exercise w.r.t sentiment classification using LSTM's (and at times in conjunction with CNN) but there the output layer can contain just 1 neuron with a sigmoid since the sentiment can either be good or bad. But if i... |
H: Input and output feature shapes in CNN for speech recognition
I am currently studying this paper and are trying to understand what exactly the input and output shape is. The paper describes an acoustic model consisting of using cnn-hmm as the acoustic model. The input is a image of mel-log filter energies visuali... |
H: Why is my neural network not learning?
I am using the Keras library (with Python 3.6) to create a neural network.
My network maintains a constant overall maximum accuracy of 62.5%, over 16 training samples.
In what ways can I increase this accuracy?
Should I increase the number of training samples, or will restric... |
H: How can I know how to interpret the output coefficients (`coefs_`) from the model sklearn.svm.LinearSVC()?
I'm following Introduction to Machine Learning with Python: A Guide for Data Scientists by Andreas C. Müller and Sarah Guido, and in Chapter 2 a demonstration of applying LinearSVC() is given. The result of c... |
H: How to detect the match precision of OneVsRestClassifier
I've improved my text classification to topic module, from simple word2vec to piped tfidf and OneVsRestClassifier (using sklearn). It does improve the classification but with word2vec I was able to calculate the match percentage for each topic and with OneVsR... |
H: Orange (Data Mining) : How to start using "Orange" from Python Anaconda Environment?
I have install "Orange Data Mining v3.4.1" in Anaconda Python v3 environment using commands : "conda install orange3" sucessfully.
However, I do not know how to call "Orange" as Application to start using it. There is also NO icon... |
H: Error While Trying To Transform Data Into Stocks Object
I am following a tutorial on R-Bloggers on an introduction to stock market data analysis. I got to this part -
if (!require("magrittr")) {
install.packages("magrittr")
library(magrittr)
}
## Loading required package: magrittr
stock_return % t % > % as.xts
he... |
H: How to use binary text classifier(built using SVM with TF-IDF) to classify new text document?
I have built binary text classifier using SVM on TF-IDF for news articles(Sports: Non-Sports).
But I not sure how to classify new document using this model. Since TF-IDF is calculated based on the occurrence of a word in ... |
H: Building a machine learning model based on a set of timestamped features to predict/classify a label/value?
I'm trying to apply machine learning to pharmaceutical manufacturing to predict whether batches of drug products manufactured are good or not. for the sake of relatability, let's use coffee brewing as an anal... |
H: Dynamic clustering for text documents
I have few hundred thousands of text documents. Some of them are pretty similar - they differ just in ex. names or some numbers, all other text is the same. I would like to cluster these documents, so when I list them, the most similar are listed together in groups. That's how ... |
H: Why don't tree ensembles require one-hot-encoding?
I know that models such as random forest and boosted trees don't require one-hot encoding for predictor levels, but I don't really get why. If the tree is making a split in the feature space, then isn't there an inherent ordering involved? There must be something I... |
H: How is PCA is different from SubSpace clustering and how do we extract variables responsible for the first PCA component?
New update:
I understand PCA components ensure we select variables responsible for high variance, but I would like to know how to extract key variables responsible only for high variance throug... |
H: MNIST Deep Neural Network using TensorFlow
I have been working on this code for a while and it gave me a lot of headache before I got it to work. It basically tries to use the mnist dataset to classify handwritten digits. I am not using the prepackaged mnist in TensorFlow because I want to learn preprocessing the d... |
H: Randomizing selection in R
I am trying to create a comparison group. So far this group contains 45 data points and I need to populate the remaining 55 (for a total of 100 data points).
These remaining 55 need to be a randomized selection supplied from a larger data set. Any recommendations for R code that would cre... |
H: Incorrect output dimension?
I am trying to start the learning of a cnn network which has 72 input and one output being a vector of length 24 stating the a class for each third input 72/24 = 3. There are 145 classes.
this is how i've designed the network currently passed my data:
print "After test_output/input"
pr... |
H: Convolutional layer dropout layer in keras
According to classical paper
http://www.cs.toronto.edu/~rsalakhu/papers/srivastava14a.pdf
dropout operation affects not only training step but also test step - we need to multiply all neuron output weights by probability p.
But in keras library I found the following implem... |
H: Should weights on earlier layers change less than weights on later layers in a neural network
I'm trying to debug why my neural network isn't working. One of the things I've observed is that the weights between the input layer and the first hidden layer hardly change at all, whereas weights later in the network (eg... |
H: Can we generate huge dataset with Generative Adversarial Networks
I'm dealing with a problem where I couldn't find enough dataset(images) to feed into my deep neural network for training.
I was so inspired by the paper Generative Adversarial Text to Image Synthesis published by Scott Reed et al. on Generative Adver... |
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