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H: How are per-layer-detected-patterns in a trained CNN plotted?
In the case my question is not clear, I am talking about the patterns that are detected in each of the layers of an image-trained Convolutional Neural Network (CNN). Take the following image as an example (by Honglak Lee). I think I understand the concep... |
H: Intuition in Backpropagation (gradient descent)
I am reading about backpropagation, one of many processes involved in gradient descent, and I couldn't quite grasp the intuition in one of the equations.
http://neuralnetworksanddeeplearning.com/chap2.html#MathJax-Element-185-Frame
An equation for the error $\delta^l... |
H: Comparing Non-deterministic Binary Classifiers
I have two classifiers which I am implementing, and they are both non-deterministic in the sense that they can each give different results (FPR and TPR) when you run them multiple times. I would like to compare these two algorithms to evaluate their performance. How do... |
H: What is the One Max Problem in detail?
I am looking a python lib named deap, but stuck at beginning.
The first paragraph says:
The problem is very simple, we search for a 1 filled list individual.
What does 1 filled list means? Search a 1 filled list, from where? individual list or individual 1?
Google One Max Pr... |
H: How to use binary relevance for multi-label text classification?
I'm trying to use binary relevance for multi-label text classification.
Here is the data I have:
a training set with 6000 short texts (around 500-800 words each) and
some labels attached to them (around 4-6 for each text). There are
almost 500 differ... |
H: ValueError:invalid literal for int() with base 10: 'No''
Trying to do a binary classification and have the class names as string but when it gives me the error mentioned in the title. I tried to give integer labels as 0 and 1, the code works perfectly fine. I tried all the suggestions from stackoverflow regarding t... |
H: POC - Get an idea to create a Predictive Model
I'm trying to look for an idea to create a predictive model having the following data:
Customer_ID - Integer
Catalog_ID - Integer
Country_Code - Integet
Year - Integet
Month - Integer
Day - Integer
Quantity_Purchased - Integer
Product_Purchased - Double
I'm trying to ... |
H: Handling time series data with gaps
I am working on a dataset with physical measurements taken daily (weight, bmi, etc...) and I am working through the process to graphically represent it. I think it is worth noting that every day has a corresponding row, but if no measurements were taken, the values are the same a... |
H: How to apply Content-based image retrieval for scanned images?
Is there a way to differentiate between scanned images(with only text) that are well-lit and with good contrast, from the ones that are not(that have poor quality), making use of Content-based image retrieval? More exactly, is there a feature extraction... |
H: NLP - why is "not" a stop word?
I am trying to remove stop words before performing topic modeling. I noticed that some negation words (not, nor, never, none etc..) are usually considered to be stop words. For example, NLTK, spacy and sklearn include "not" on their stop word lists. However, if we remove "not" from t... |
H: Performance and architecture of neural network for increased dimensions
I posted this question on Cross Validated before I realized that this existed. I think it is better suited here and got no answers over there so I have deleted other post. I have reproduced the question below:
I have been playing around with t... |
H: Loss function for sparse tagging
I am writing a musical transcription system with a RNN (LSTM).
Input: 1 vector of features per timestep (about 40 timesteps in a second)
Output: 1 binary vector of notes per timestep (dimension=36) (1 is on, 0 if off).
Model : LSTM(512) + LSTM(256) + Dense(36, activation='sigmoid')... |
H: Machine Learning: Writing Poems
I'm a student of machine learning, and these days I was trying to learn how to use the TensorFlow library. I've gone through various tutorials and trial&errors with tensorflow, and I thought the best way to learn it for real would be to make use of it in a little project of my own.
I... |
H: An abstract idea for the performance diffs between SLP and MLP
Recently I am working on some predictive analytic which based on neural network.
When I tried some tests on MLP with one hidden layer or multiple hidden layers, the results showed that:
one hidden layer performance on prediction is always better than m... |
H: shape of theano tensor variable out of keras Conv2D
Being new to theano, pls bear with me. I thought the shape of the tensor variable is already well defined out of the Conv2D layer since the input is specified, as follow,
from keras.layers import Input, Convolution2D
import theano
input_img = Input(shape=(1, 28, 2... |
H: How to compute the Jaccard Similarity in this example? (Jaccard vs. Cosine)
I am trying to understand the difference between Jaccard and Cosine. However, there seem to be a disagreement in the answers provided in Applications and differences for Jaccard similarity and Cosine Similarity.
I am seeking if anyone coul... |
H: Pickled machine learning models
Is there a website where people store their pickled models for others to try? E.g. different people might try different ML approaches on the iris dataset, is there a place where I can find/download models others have constructed?
AI: On Kaggle.com, there is a datasets section. In thi... |
H: Rank feature selection over multiple datasets
Through backward elimination I get a ranking of features over multiple datasets. For example in the dataset 1 I have the following ranking, the feature in the top being the most important:
feat. 1
feat. 2
feat. 3
feat. 4.
...
, whereas for dataset 2 I have for examp... |
H: Reinforcement learning: understanding this derivation of n-step Tree Backup algorithm
I think I get the main idea, and I almost understand the derivation except for this one line, see picture below:
I understand what we're doing by using the policy probability to weight the rewards from time t + 2 (because gettin... |
H: Principal Component Analysis, Eigenvectors lying in the span of the observed data points?
I have been reading several papers and articles related to Principal Component Analysis (PCA) and in some of them, there is one step which is quite unclear to me (in particular (3) in [Schölkopf 1996]).
Let me reproduce their... |
H: Algorithm for generating rules for classifying documents
Im looking for an algorithm that can deduct a set of rules based on a dataset of "training documents" that can be applied to classify a new unseen document. The problem is that I need these rules to be viewable by the user in the form of some string represent... |
H: How to get summary statistics in Orange?
I just started using Orange, and am having trouble finding how to get basic summary statistics, like the n (count), average, and standard deviation.
Is there a widget that does this and I'm simply overlooking it?
AI: I found 3 ways to do it :
you have to use the Data Info w... |
H: Finding out the scale when using MinMaxScaler()
I am using the MinMaxScaler() of sklearn to scale my features before using kmeans.I needed to find the scale used.
from sklearn import preprocessing
scaler = preprocessing.MinMaxScaler()
scaler= scaler.fit_transform(finance_features)
print scaler.scale_
However on us... |
H: How can I fill NaN values in a Pandas DataFrame in Python?
I am trying to learn data analysis and machine learning by trying out some problems.
I found a competition "House prices" which is actually a playground competition. Since I am very new to this field, I got confused after exploring the data. The data has ... |
H: adjust output from normalization?
I've trained a neural network network that given a minmax normalized input, provides a minmax normalized output.
this might be late, but is it possible from a minmax normalized output to create the actual output, given you know the actual min and max value?
so an unormalized outpu... |
H: What is "noise" in observed data?
I am reading pattern Recognition and machine learning by Bishop and in the chapter about probability, "noise in the observed data" is mentioned many times. I have read on the internet that noise refers to the inaccuracy while reading data but I am not sure whether it is correct. SO... |
H: Reducing a page of content to a short paragraph
I remember years ago, Yahoo detailed how they were able to reduce a webpage down to a short paragrah of text succently summarising the content in sentences, as opposed to a list of keywords. What is this called? Are there any open / free code to do this?
AI: Look into... |
H: Measuring Difference Between Two Sets of Likert Values
I asked users to complete a likert survey (1-5) at the start of an activity, and conclusion of the activity. What is the best manner to show the rate of change/difference between these two result sets? I was considering a Pearson correlation, but after thinking... |
H: Reducing sample size
I have a large dataset (around $ 10^6 $ samples) and an algorithm that will surely choke on that much data.
Suppose that I have removed duplicates and near-duplicates. What are the well-known techniques for reducing sample size without losing too much of the information possibly encoded in the ... |
H: When is something a Deep Neural Network (DNN) and not NN?
When would a neural network be defined as a Deep Neural Network (DNN) and not a NN?
A DNN as I understand them are neural networks with many layers, and simple neural networks usually have fewer layer... but what a many and a few in numbers? or is there some... |
H: Why is learning rate causing my neural network's weights to skyrocket?
I am using tensorflow to write simple neural networks for a bit of research and I have had many problems with 'nan' weights while training. I tried many different solutions like changing the optimizer, changing the loss, the data size, etc. but ... |
H: analogy for pearson r statistics for binary classification task
I am trying to get idea how variables of my data correspond to target variable (binary class).
In regression, Pearson r statistic is quite good to get sense of variable relationship. Also I can use it for classification, treating classes 0 and 1 as rea... |
H: CSR scipy matrix does not update after updating its values
I have the following code in python:
import numpy as np
from scipy.sparse import csr_matrix
M = csr_matrix(np.ones([2, 2],dtype=np.int32))
print(M)
print(M.data.shape)
for i in range(np.shape(M)[0]):
for j in range(np.shape(M)[1]):
if i==j:
... |
H: What are recommended ways\tools for processing large data from Excel Files?
A Very Happy New Year! I'm currently working on an analytics project with large volumes of data stored in excel files (about 50GB in 1000 files). The files use a custom formatting to store date-time data to the millisecond. The processing a... |
H: How to determine feature importance while using xgboost in pipeline?
How to determine feature importance while using xgboost (XGBclassifier or XGBregressor) in pipeline?
AttributeError: 'Pipeline' object has no attribute 'get_fscore'
The answer provided here is similar but I couldn't get the idea.
AI: As I found,... |
H: DTW (Dynamic Time Warping) requires prior normalization?
I'm trying DTW from mlpy, to check similarity between time series.
Should I normalize the series before processing them with DTW? Or is it somewhat tolerant and I can use the series as they are?
All time series stored in a Pandas Dataframe, each in one column... |
H: Problem when loading a XGBoost model in a different computer
I'm working on a project and we are using XGBoost to make predictions. My colleague sent me the model file but when I load on my computer it don't run as expected.
When I changed one variable from the model from 0 to 1 it didn't changed the result (in 200... |
H: LSTM for capturing multiple patterns
I am trying to use an LSTM to predict daily usage for users. I have data for (say) 90 days of usage for a large number of users. Based on business knowledge (and initial analysis) we know users fall roughly into different categories. E.g. daily users would have a non-zero usage ... |
H: Is feature selection necessary?
I would like to run some machine learning model like random forest, gradient boosting, or SVM on my dataset. There are more than 200 predictor variables in my dataset and my target classes are a binary variable.
Do I need to run feature selection before the model fitting? Does it aff... |
H: What knowledge do I need in order to write a simple AI program to play a game?
I'm a B.Sc graduate. One of my courses was 'Introduction to Machine Learning', and I always wanted to do a personal project in this subject.
I recently heard about different AI training to play games such as Mario, Go, etc.
What knowledg... |
H: Computing weights in batch gradient descent
I have a reasonably large set of images that I want to classify using a neural network. I can't fil them all into memory at once, so I decided to process them in batches of 200. I'm using an cross-entropy cost function with a minimization algorithm from numpy.
My question... |
H: Instead of one-hot encoding, can I store the same information in one column using a single value?
Rather than creating 15 additional columns full of sparse binary data, could I:
1) use the first 15 prime numbers as indexes for the 15 categories
2) store data by multiplying the prime numbers of the categories that ... |
H: Which book is a standard for introduction to genetic algorithms?
I have heard of genetic algorithms, but I have never seen practical examples and I've never got a systematic introduction to them.
I am now looking for a textbook which introduces genetic algorithms in detail and gives practical examples how they are ... |
H: Is the probabilistic cutoff in random forest flexible?
I fit the random forest to my dataset with a binary target class. I reset the probabilistic cutoff to a much lower value rather than the default 0.5 according to the ROC curve. Then I can improve the sensitivity (recall) but meanwhile sacrificed the precision.
... |
H: Mapping sequences of different lengths to fixed vector - Python
I am trying to make a chatbot using a deep neural network in python using keras. The problem I am having is that for the deep neural network to work, the input dimension has to be fixed. So my question is, how can I map a sequence of words (sentence of... |
H: which machine learning technique can be used?
I want to understand the intent of the customer using his search queries, let's say if a customer is interested in yoga pants, he can either search for yoga pants or exercise pants or workout tights etc. Is there a model that I can use to find out all the search keyword... |
H: The model performance vary between different train-test split?
I fit my dataset to the random forest classifier and found that the model performance would vary among different sets of train and test data split. As what I have observed, it would jump from 0.67 to 0.75 in AUC under ROC curve (fitted by the same model... |
H: How to calculate VC-dimension?
Im studying machine learning, and I would like to know how to calculate VC-dimension.
For example:
$h(x)=\begin{cases} 1 &\mbox{if } a\leq x \leq b \\
0 & \mbox{else } \end{cases} $, with parameters $(a,b) ∈ R^2$.
What is the VC-dimension of it?
AI: The VC dimension is an estimate f... |
H: Is the graphic of deep residual networks wrong?
I am currently wondering if the following graphic of deep residual networks is wrong:
I would say the graphic describes
$$\varphi \left (W_2 \varphi(W_1 x) + x \right ) \qquad \text{ with } \varphi = ReLU$$
The $\mathcal{F}(x)$ does not make sense to me. Assuming bot... |
H: What is the procedure to create a bag of visual words model with SIFT?
I have more than 1500 black and white classified images in a training set and I want to create a probabilistic model to classified new images. To be more explicit, given a new black and white image, my model has to predict:
animal: 84%
vegetal: ... |
H: the feasibility of image processing techniques for physics based images
When building deep learning models for image analytics-related applications, we sometimes apply various types of operations to enhance the image, such as an image denoising operation.
In my study, we have images generated by physical simulation... |
H: R data frame create a new variable which corresponds to one of the existing one
Currently this is what I get. "community_area_clean" is the new variable that I added by extracting a variable that lists all the communities from a data frame. "CommArea_Name" is the original "unclean" variable. But I find that the na... |
H: In text classification, how can I use a neural network on word embeddings?
I have read some papers on text classification but they are pretty abstract. I fail at understanding how to train a multi layer perceptron with data made of sentences -> label.
A perceptron takes a vector input of size m and outputs a vector... |
H: In XGBoost would we evaluate results with a Precision Recall curve vs ROC?
I am using XGBoost for payment fraud detection. The objective is binary classification, and the data is very unbalanced. One out of every 3-4k transactions is fraud.
I would expect the best way to evaluate the results is a Precision-Recall... |
H: Binary classification problem
Im new to ML, I have a data set for Music sales info for Vinyls, the data set contains:
Author
Album Title
Genre
Country
RevenueGenerated
AverageRevenueGenerated
My goal is to create a Model which I can help me understand which Music may generate a lot of revenue (Boolean). I creat... |
H: Extending a trained neural network for a larger input
I have a seq2seq conversational model (based on this implementation) trained on the Cornell movie dialogs.
Now I want to fine-tune it on a much smaller dataset. The new data comes with the new words, and I want UNKs for as few new words as possible. So I'm going... |
H: Difference between subgradient SVM and kernel SVM?
What is the difference between subgradient svm and kernel svm?
From my understanding subgradient svm is a linear classifier that uses hinge loss and kernel svm uses some kernel function for non linear classification. I was wondering, if subgradient is only a line... |
H: How to use ensemble of models in FM or FFM?
I am using Factorization Machines ( libfm) and also the Field Aware Factorization Machines (libffm) for a kaggle competition. I am currently using the single models of each respectively for prediction.
I came to know that we can use ensemble of models for both FM and FF... |
H: Normal equation result simplification
The derivation of the normal equation can be noted
$\theta = (X^TX)^{-1}(X^T)y$, where $X^{-1}$ is the inverse of $X$ and can also be written $inv(X)$.
But why can't we write $inv(X^T X)$ as $inv(X)inv(X^T)$, and also use the definition of inverse $inv(X^T)(X^T) = I$?
Then $... |
H: Neural Network accuracy and loss guarantees?
This question is part of a sample exam that I'm working on to prepare for the real one. I've been stuck on this one for quite a while and can't really motivate my answers since it keeps referring to guarantees, can someone explain what guarantees we can have in a neural ... |
H: Classification problem approach with Python
I am a Python beginner, just getting into machine learning and need advice on the approach i should use for my problem.
Here is an example of my data-set.
Where the RESULT is a corresponding INDEX in each VALUES array and every row is a separate array, i need to find the... |
H: My ADALINE model using Gradient Descent is increasing error on each iteration
I have used the Iris Dataset's 1st and 3rd Column for the features. and the labels of Iris Setosa (-1) and Iris Versicolor (1). I am using ADALINE as a simple classification model for my dataset. I am using gradient descent as the cost mi... |
H: Re-bucket weekly sales data and calculate descriptive statistics
I have sales data in weekly buckets like this:
weekID product SoldQty
1 1 10
2 1 20
3 1 30
4 1 40
5 1 50
6 1 60
7 1 70
1 2 10
2 2 20
Calculating the s... |
H: Words to numbers faster lookup
I'm training an LSTM for sentiment analysis on a review dataset downloaded from here. The music review dataset contains about 150K data points (reviews of varying length labelled pos or neg). After creating a dictionary, I'm running a script in Python to replace strings (words) with n... |
H: What is a tower?
In many tensorflow tutorials (example) "towers" are mentioned without a definition. What is meant by that?
AI: According to tensorflow documentation about CNN,
The first abstraction we require is a function for computing inference and gradients for a single model replica. In the code we term this ... |
H: Using a K-NN Classification Approach for Time Series Data?
I have a dataset which contains time-series data of water flow over time. I have a flow meter connected to a kitchen faucet, and I am trying to cluster or classify specific water usage events.
The data is collected every second, and in each row I am given ... |
H: Python SVM rgb cluster
This is the distribution of my data.
I want to use SVM with only one 'circle' to cluster most of the 0.
I tried to run it with the code
clf = svm.SVC(max_iter=1, kernel='rbf')
However, it gives a strange result
How should I do it correctly?
Data:
X
array([[ 5.46787217e+00, 2.09073426e-0... |
H: Pattern Recognition on Financial Market
Which machine learning or deep learning model(has to be supervised learning) will be best suited for recognizing patterns in financial markets ?
What I mean by pattern recognition in financial market :
Following Image shows how a sample pattern (i.e. Head and shoulder) looks ... |
H: KMeans clustering to help label Multi-class Supervised model
EDITED:
Is it accepted practice to be able to use a KMeans clustering algorithm to help label data fed into a supervised model? (Unsupervised --feeds-> supervised)?
The reason being, relabeling millions of records is not possible and it is a class imbalan... |
H: Why the number of neurons or convolutions chosen equal powers of two?
In the overwhelming number of works devoted to the neural networks, the authors suggest arhitechure in which each layer is a numbers of neurons is power of 2
what are the theoretical reasons(prerequisite) for this choice?
AI: Deep Neural Networks... |
H: How is a single element of the training set called?
This question is only about the vocabulary.
Do / can you say
data item
data sample
recording
sample
data point
something else
when you talk about elements of the training / test set? For example:
The figure shows 100 data items of the training set.
Database A c... |
H: What is context window size?
I am trying to implement a recurrent neural network machine translation system, and I am just learning the things.
I am creating a word embedding matrix. In order to do that, I should know my vocabulary size, dimension of the embedding space, and context window size?
What is context win... |
H: Machine Learning vs Deep Learning
I am a bit confused by the difference between the terms "Machine Learning" and "Deep Learning". I have Googled it and read many articles, but it is still not very clear to me.
A known definition of Machine Learning by Tom Mitchell is:
A computer program is said to learn from exper... |
H: Does Tensorflow uses vectorization in its operators
I'm kinda new to tensorflow and just wanted to know if it already performs vectorization in its operators like multiplying matrices and so on.
And if not if its doable.
As an example let's say we have 2 matrices and we want to multiply them. Instead of for loops t... |
H: How to calculate accuracy on keras model with multiple outputs?
I have a keras model that takes in an image with (up to) 5 MNIST digits and outputs a length and then (up to) 5 digits. I see that model.evaluate() reports accuracies for each of the outputs but how do I determine how good the model is at predicting th... |
H: Recommender System: how to treat different events
I'm trying to build recommender based on user history from e-commerce. There are two(potentially more) types of events: purchase and view.
Is it okay to sum up number of purchases and views for a given item(with purchase and view having different weights)? Or I`ll j... |
H: Machine Learning - Range of Hypothesis space and choiceof Hypothesis function type
I am new to machine learning and seek your help in clarifying my elementary doubts. I did a fair amount of googling, but find most literature jumping directly into math.
What I know is that given a labelled training data, a ML algor... |
H: Organize TSNE data into grid
I have some data reduced by TSNE into a 2D representation, which shows clear spatial features.
However, I'd like to format this into a grid – not just snapping data to the nearest grid square but spreading everything out to fill up a grid, preserving (as much as possible) the existing ... |
H: Feature extraction from web browsing history of one website
I have a dataset of web browsing histories for users visiting a particular website over a period of time (say the last 90 days). Each user has a unique ID and several records showing when he/she visited a particular page on the website.
It looks like follo... |
H: Is Keras useful for professionals?
I know that Keras is developed for quick deployment. Is it just for beginners or also useful in industry for professionals?
AI: Keras is used in academia (see google scholar citations of Keras as a proxy for academy adoption) and hobbyists (see github stars or google results for k... |
H: Clustering high dimensional data
TL;DR: Given a big image dataset (around 36 GiB of raw pixels) of unlabeled data, how can I cluster the images (based on the pixel values) without knowing the number of clusters K to begin with?
I am currently working on an unsupervised learning project to cluster images; think of i... |
H: The effect of an linear layer?
I have the last couple of month worked with an regression problem, of turning a framed audio file into a set of mfcc features, for a speech recognition application
I tried a lot different network structures, Cnn, different normalisation techniques, different optimizer, adding more la... |
H: handling missing data in pandas python
I have to impute missing values in the column named <Age> with the mean of the nearest available values above and below in the column <Age>.
If the Age column had values in order
NA,7,6,NA,7,8,NA,NA,NA,10,5,NA,NA,5,9,9,12,8,6,NA,NA
After imputation, column should look like
7,... |
H: Feed forward neural network, output as list of targets and associated probabilities
I am working through an FNN tutorial, right now it outputs a sigmoid probability from 0-1 (0.8956 for example). My own data has 3+ possible targets so i need the output to be a list of the targets and the associated probability for ... |
H: Modern Feature Selection Review/Resources
I found this review paper by Guyon and Elisseeff in a 2003 JMLR publication but, although not outdated, it is quite old. Is there a more recent review or resource on the topic of feature selection?
JMLR Review 2003
AI: I looked into it quite recently and found these papers:... |
H: What is the difference between data-driven methods and machine learning?
I was wondering (about a more semantic question), is there a difference between data-driven methods and machine learning? Or is it more correct to state that machine learning is a category of data-driven methods (and what then are other catego... |
H: Reason for square images in deep learning
Most of the advanced deep learning models like VGG, ResNet, etc. require square images as input, usually with a pixel size of $224x224$.
Is there a reason why the input has to be of equal shape, or can I build a convnet model with say $100x200$ as well (if I want to do facI... |
H: Benefits of stochastic gradient descent besides speed/overhead and their optimization
Say I am training a neural network and can fit all my data into memory. Are there any benefits to using mini batches with SGD in this case? Or is batch training with the full gradient always superior when possible?
Also, it seems... |
H: Do convolutions "flatten images"?
I'm looking for a good explanation of how convolutions in deep learning work when applied to multi-channel images. For example, let's say I have a 100 x 100 pixel image with three channels, RGB. The input tensor would then have dimensions 100 x 100 x 3.
If I apply a convolution w... |
H: Can the output of convolution on image be higher than 255?
I have probably a very simple question. When I convolve an (grayscale) image using some kernel I get some output. The original pixel can be only between 0 and 255. Is possible that the output of a convolution can be higher? Because we are creating feature m... |
H: Ad click prediction: what are the negative examples?
I am analysing the log of a website and I would like to build a classifier to predict the users that are likely to click on an Ad.
The Ad can be displayed to the visitor several times.
To build any classifier I need positive and negative examples:
The positives ... |
H: Why isn't leaky ReLU always preferable to ReLU given the zero gradient for x<0?
It looks to me like the leaky ReLU should have much better performance since the standard ReLU can’t use half of its space (x < 0 where the gradient is zero). But this doesn't happen and in practice most people use standard ReLU.
AI: On... |
H: Unable to open .json file in pandas
I want to convert a json file into a dataframe in pandas (Python). I tried with read_json() but got the error:
UnicodeDecodeError:'charmap' codec can't decode byte 0x81 in position 21596351:character maps to <undefined>
I think I have some unwanted data in the json file like n... |
H: Found input variables with inconsistent numbers of samples
I would appreciate if you could let me know how to resolve this error:
Code:
X = np.array(pd.read_csv('my_X_table1-1c.csv',header=None).values)
y = np.array(pd.read_csv('my_y_table1-1c.csv',header=None).values.ravel())
X_train, X_test, y_train, y_test = tra... |
H: Gamma random variable , need to find the approximate 90th percentile of X?
A colleague defines a random variable $X = \frac{Z}{Y^2}$, where $Z$ is a known normal random variable, $Y$ is a known gamma random variable, and $Z$ and $Y$ are independent of each other.
You are not able to get an analytical form for the ... |
H: Is standardization needed before using scikit-learn SVM?
I am using the SVM function provided by scikit-learn. I would like to know whether I need to perform standardization before fitting the model. As I know, LibSVM tends to require pre-processing the data. I am not sure whether scikit-learn automatically normali... |
H: Confused about how to apply KMeans on my a dataset with features extracted
I am trying to apply a basic use of the scikitlearn KMeans Clustering package, to create different clusters that I could use to identify a certain activity. For example, in my dataset below, I have different usage events (0,...,11), and eac... |
H: Using Pandas to_numeric() in Azure Machine Learning Studio
I am facing an issue that Azure Machine Learning Studio fails to find the to_numeric method in pandas.
After reading a .csv in AMLS I try to process it in a python script. The line that is throwing me an error is:
dataframe1['Monthly Debt'] = pd.to_numeric(... |
H: Text processing
I am completely new to analyze cluster texts, I'm using Goodreads API to get Books synopsis.
My goal is to group similar books, for example:
Politics
Music
Biographies
etc...
While Goodreads provide genre, I would like to use synopsis and use the text for this.
Lets say I will get N books synopsis... |
H: What does "batch" and "batch_size" mean in word2vec skip-gram model?
I am reading tensorflow documentation now and I can not understand what does "batch" and "batch_size" mean in explanation skip-gram model. Please, can someone explain me?
Here this paragraph:
Recall that skip-gram inverts contexts and targets, an... |
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