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H: Why do we need to handle data imbalance?
I would like to know why we need to deal with data imbalance. I know how to deal with it and different methods to solve the issue - by up sampling or down sampling or by using SMOTE.
For example, if I have a rare disease 1 percent out of 100, and lets say I decided to have a... |
H: Learning Algorithm that decide which model gives better results for each testing instance
Is their any existing Ensemble technique which uses subset of training data to predict which algorithm is better for predicting each instance of testing data?
Let's say we have N sized training set and K sized testing set in w... |
H: Use of TfidfVectorizer on dataframe
I have the dataframe which has two colums(Reviews and Label):
Reviews Label
0 [cameron, diaz, woman, marri, judg, play] 1
1 [turgid, dialogu, feebl, character, harvey] 0
2 [misfortun, watch, rubbish, sky, cinema] 1
I want to ap... |
H: Goodhart's law applied to data science
I recently learned about Goodhart's Law. Simply put,
When a measure becomes a target, it ceases to be a good measure.
However, in Data Science, we really do aim at improving our performance by increasing or decreasing a metric, and improve our models based on that. For insta... |
H: How can I find contextually related words and classify into custom tags/labels?
PROBLEM:
Suppose if I have a small dataset containing some words and their tags/labels.
The main task is to provide tags to other words(which are not in the dataset) based on their contextual relationship with the words already in the d... |
H: MLP incremental learning
In my project I use 2 MLP ANNs: for classification and for prediction. Basic training dataset is stored in database (MS SQL Server). But we need to make future incremental learning possible. It means that ANN is used in industrial realtime system, operator marks observations in database as ... |
H: Finding similar articles in realtime
I want to build a large document (news article) searchable database, such as when adding a new article I will be able to quickly find X most similar articles from it.
What is the right tech/algorithm/Python framework to approach this?
AI: Elasticsearch is the right tool to use i... |
H: In supervised learning, why is it bad to have correlated features?
I read somewhere that if we have features that are too correlated, we have to remove one, as this may worsen the model. It is clear that correlated features means that they bring the same information, so it is logical to remove one of them. But I ca... |
H: Regex remove 1-2 character sequences: hyphens literal, not word boundaries
I need a regex in R to exclude 1 or 2-character words, but which does not treat hyphens as word boundaries. Here is an example:
z <- c("regulatory protein SR-B1 na na na na", "Dr Foo is na Editor-in-chief", "na P3 protein is popular na na")... |
H: How to give CIFAR-10 as an input to MLP
I am a noob in machine learning and trying to build a classifier using keras by following this tutorial machine learning mastery tutorial
I want to build a classifier based on MLP like in classification of MNIST using MLP for CIFAR-10 data set.Like in MNIST data set the 28*2... |
H: Does torch.cat work with backpropagation?
I was wondering if it was okay to use torch.cat within my forward function. I am doing so because I want the first two columns of my input to skip the middle hidden layers and go directly to the final layer.
Here is my code: you can see that I use torch.cat at the last mome... |
H: Should the bias value be added after convolution operation in CNNs?
Should we add bias to each entry of the convolution then sum, or add bias once at end of calculating the convolution in CNNs?
AI: Short answer: the bias is added once after the convolution has been calculated.
Long answer: discrete convolution that... |
H: What is average unpooling?
I'm working on an implementation of a paper and I haven't been able to find a description of average unpooling. I tried using max unpooling instead and my results were not great.
Thanks!
AI: When you go backward for max-pooling you keep track of the position of the maximum:
$$ X = \begin{... |
H: Character-based word representation using bi-lstm
In this blog, it teaches us how to get a word embedding using bi-lstm in character level like the image below:
I am wondering how to optimize the word vector from character-based approach. Is there any loss function or any strategy to update or optimize the word ve... |
H: Does gradient descent always converge to an optimum?
I am wondering whether there is any scenario in which gradient descent does not converge to a minimum.
I am aware that gradient descent is not always guaranteed to converge to a global optimum. I am also aware that it might diverge from an optimum if, say, the st... |
H: Independence/correlation test between features (not feautre-label)
I'm doing a Naive Bayes prediction model where I've 666 features to select from.
I've tried the SelectKBest chi2 test but it's a features-label test whereas what I'm trying to do is to find out the independency and also correlation feature-features.... |
H: Contemporary alternatives to SIFT for image feature extraction?
I've been learning about SIFT and all the ways its descriptors can be used to do different tasks.
I am particularly interested in the way SIFT can be used for image classification. (e.g. A 2006 paper by Niester & Stewenius relies on SIFT descriptors to... |
H: Neural network predicted value
I am starting to learn about machine learning as a whole and have found a big interest in Neural Networks. My question today is,
Given a simple cost function $J$ with weights $w1, w2$ and inputs $m1, m2$ and a target prediction/error $b$ so that $J = w1*m1 + w2*m2 + b$.
Lets say we w... |
H: Is training one epoch using mini-batch gradient descent slower than using batch gradient descent?
I wonder whether one epoch using mini-batch gradient descent is slower than one epoch using just batch gradient descent.
At least I understand that one iteration of mini-batch gradient descent should be faster than one... |
H: Cost Function on non linear noisy data
I was curious to see if one can use a cost function on a set of data points to find the "optimial minimum" solution for any given set of data.
I know for a regular set of data that is clustered symmetrically following a straight regression line is easy to find the proper cost... |
H: Convolution Neural Network Loss and performance
I have a set of about ~100,000 training examples. Ratio of positive to negative example is roughly 1:2. The true ratio is more like 1:100 so this represents a major downsampling of the negative class. It is also a very noisy dataset - the examples were automatically g... |
H: ReLU activation function outputs HUGE numbers
I have FINALLY been able to implement backpropagation, but there are still some bugs I need to fix. The main is issue the following: My ReLU activation function produces really big dJdW values (derivative of error function wrt weights). When this gets subtracted from ... |
H: Do Convolution Layers in a CNN Treat the Previous Layer Outputs as Channels?
Lets say you have a max pooling layer that gives 10 downsampled feature maps. Do you stack those feature maps, treat them as channels and convolve that 'single image' of depth 10 with a 3d kernel of depth 10? That is how I have generally t... |
H: Clamping Q function to it's theoretical maximum, yes or no?
I'm implementing DQN algorithm from scratch on MountainCar simulation.
I'm using a setup of $reward = 1.0$ when car hits the flag, and $0$ otherwise.
Reward decay factor is set to $\gamma=0.99$. Algorithm starts with exploration factor of $\epsilon = 1.0$... |
H: Is it possible to use Recurrent NN (LSTM) for classification?
I have a dataset C of 50,000 (binary) samples each of 128 features. The class label is also binary either 1 or -1. For instance, a sample would look like this [1,0,0,0,1,0, .... , 0,1] [-1]. My goal is to classify the samples based on the binary classes(... |
H: Imbalanced class with same rows?
In my dataset i have 3 classes-> 0,1,2.
0(72k),1(13k)and 2(13K) in brackets are there count.
So whenever i try to predict them with any algorithm ,i observed that almost all the "2"'s are predicted as "0".
On little exploration i found that there are some rows where attributes of 0... |
H: Using a decision tree with 3 dimensional input points
I implemented a normal classification tree (that uses the Gini index to look for a split). I am using it to predict the age of people. My input data was a series of points on 1 axis (Only X coordinate), and output was an age (9 years old, 10 years old....).
Exam... |
H: Create a Predictive model to find users that would book an exam
I'm currently working for a health company in Brazil, and I want to create a Predictive model that would find users that are one step close to book an appointment.
We currently have 1 million visits per month, and 60% of this visits are not booking any... |
H: Cleaning time series data
I have a time series data about daily usage of a computer program, here is an example
2017-11-10: 0
2017-11-09: 14
2017-11-08: 0
2017-11-07: 6
2017-11-06: 102
2017-11-05: 0
2017-11-04: 0
As you can see 11-06 has a spike at 102. Due to our way of gathering this data, we know that data is ... |
H: Conv1D to predict winner of two feature sets
I'm trying to predict the winner of a race, when given 2 sets of features. The data looks like this:
array([[[ 1. ],
[ 1. ],
[ 0. ],
[ 0.10447761],
[ 0.18892762],
[ 0.76190472],
[ 1. ],
[... |
H: Bias in Naive Bayes classifier
I am building a document classifier using Naive Bayes. There are 10 classes. My question is that :
1 Should each class contain the same number of documents for training?
What if the number of training example in each class is different?
2 Does the number of classes and classificatio... |
H: How to retrain the neural network when new data comes in?
I am new to deep learning. Can anybody help me with the online learning implimentation for deep learning models. As per my understanding, i can save a keras/tensorflow model after training and when new data comes in, i can reload the network back and retrain... |
H: Python inserts newline by writing to csv
I am trying to scrape http://www.the-numbers.com/movie/budgets/all
but when I write the table into a csv file, there is an additional line with the counter index written in between each movie row... how can I get rid of this? I dont understand how that counter line is being ... |
H: Applications of Neural networks?
I am currently learning about Nueral Networks in Machine Learning and think it very interesting but I don't really know any other Applications NN have other than in Machine Learning and AI. I have tried researching these things but have come up short.
Could anyone tell me if you co... |
H: Confusion with cosine similarity
In information retrieval when we calculate the cosine similarity between the query features vector and the document features vector we penalize the unseen words in the query.
Example if we have two documents with features vectors
d1 = [1,1,1,0,0]
d2 = [0,1,1,1,0]
We can see t... |
H: Is Neural Style Transfer considered supervised or unsupervised learning?
As far as I understand it, the Neural Style Transfer uses a content image and a style image, and generate a new image based on the two images.
It tries to find a set of pixel values such that the cost function J(C, S) is minimized. It does not... |
H: New to data Science. Which techniques best to use Large data set in insurance company?
Dataset Features
Insurance underwriting dataset for 8 years.
age
location
amount insured
some other features...(medical evidence)
Not all feature will be available to all applicants.
Target Variable
Decision on whether the a... |
H: Error when running RGFClassifier
I recently tried to run Regularized Greedy Forest algorithm (rgf Classifier) from this package https://pypi.python.org/pypi/rgf_python.
I did run pip install rgf_python, but when I tried to run the example this error pops out in spyder:
File "C:\Users\me\Anaconda3\lib\site-package... |
H: Feature selection by overfitting a small sample size
I am using a CNN based model to do sequence classification. Since training an entire dataset is very expensive, and I have a large set of features needed to try, its impossible for me to select features by full trainings.
Usually a good sanity check before traini... |
H: What is the rationale to use weights and biases in a neural network?
Searched a lot of research papers, blogs and videos but couldnt find an acceptable answer for choosing the weights and biases in neural network. Few people have mentioned to use weights randomly but if that is the case isnt that is uncertain (fuzz... |
H: How to correctly interpret the table function to determine logistic regression accuracy?
I have a set of data, that gives the length of a species of abalone, and its corresponding type (male, M, female, F, or infant, I). (https://archive.ics.uci.edu/ml/datasets/abalone)
I have constructed a logistic regression to c... |
H: One hot encoding alternatives for large categorical values
I have a data frame with large categorical values over 1600 categories. Is there any way I can find alternatives so that I don't have over 1600 columns?
I found this interesting link.
But they are converting to class/object which I don't want. I want my fin... |
H: Classifying with certainty
I'm trying to classify a binary sample with Keras and I would like to classify as many correctly as possible, while ignore the ones where the model is not sure.
The fully connected Nerual network currencly achieves around 65% but I would like to get a higher result of correctly classified... |
H: Wrong Graph Plot using K-Means in Python
This is my first time implementing a Machine Learning Algorithm in Python. I tried implementing K-Means using Python and Sklearn for this dataset.
from sklearn.cluster import KMeans
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
# Importing the ... |
H: How to add bias consideration into logistic regression code?
I am a complete beginner in coding and machine learning, and I've been tasked with learning what's under the hood of logistic regression (so I have pieced together the python code below) but I've been asked to figure out how to add bias into this code. I'... |
H: How to add more theta parameters into my logistic regression?
I am a complete beginner in machine learning and coding in python. I have been tasked with coding logistic regression from scratch in comparison with using sklearn. My question is, with my code below I believe I have set the number of thetas I want with:... |
H: Features standardization - Multilayer perceptron
I have serious doubts concerning the features standardization done before the learning process of a multilayer perceptron.
I'm using python-3 and the scikit-learn package for the learning process and for the features normalization.
As suggested from the scikit-learn ... |
H: Handling data imbalance and class number for classification
1 Is there a way to handle data imbalance? ie if data in each class for training is not balanced, say some classes have 50 documents some other have 200 documents. How to handle this?
2 How to handle the classification problem with a large number of classe... |
H: Classification based on a Clustering Result
Here is the Sample data:
Values Attribute1 Attribute2 Attribute3 Attribute4
2.5 1980 A 1.5 C
1.8 2000 A 0.4 B
12.4 2017 S 18.5 D
0.4 1... |
H: Reading a CSV in TensorFlow RNN
I am just starting off with TensorFlow and trying to implement an RNN for a dataset which consists of 11 Features (all numeric). These features will be used to predict the output of another column.
I am currently lost on where to start and tho I am able to understand how a RNN funct... |
H: Python Pandas - Interpolation with fixed value
Say we have a pandas series with the following values
[np.nan, np.nan, 1, np.nan, 2, np.nan]
What is the most efficient way fill the nan value with 0 in the middle. so we have
[np.nan, np.nan, 1, 0, 2, np.nan]
In other word, how to we do interpolation with a fixed ... |
H: Non-convex feasible region in a linear programming problem
Problem: I am working on a linear programming problem, i.e. a linear objective function to minimize:
$\mathbf{c}\cdot\mathbf{x}$,
where $\mathbf{c},\mathbf{x}\in\mathbb{R}^{N}$
Subject to constraints:
$\mathbf{x}\geq 0$ and $\mathbf{A}\mathbf{x} \leq \m... |
H: Modeling Grocery Store Transactions
I'm fiddling around with some data that represent grocery store transactions. The data are in the following form:
Each row represents a final transaction by a customer, with a column for user ID, timestamp of purchase, and basket contents. For example:
| ID | Timestamp | ... |
H: Decision tree ordering
I am interested in finding out how decision trees chose the order in which they split. I understand that splitting is based in information gain. The attribute with the lowest information gain is chosen as the root node.
If I had a data set with columns:
credit standing
age
income,
marriage s... |
H: User based recommendation factoring in user data
The question is:
what algorithms (and libraries) should i use if i want to build a recommender system with the following data in mind representation:
USER_ID ZIP Movie1 Movie2 Movie3
1 2483 5 0 3
2 2483 4 1 5
3 2345 3 1 5
Basically i want to factor i... |
H: Time Series prediction using LSTMs: Importance of making time series stationary
In this link on Stationarity and differencing, it has been mentioned that models like ARIMA require a stationarized time series for forecasting as it's statistical properties like mean, variance, autocorrelation etc are constant over ti... |
H: Comparing 2 data frames, if value is present replace with 1 or else 0
nrow(df1$v1) = 63849
nrow(df2$v2) = 3244
ifelse(df1$v2 == df$v1, 1, 0)
I know this is an easy question but I tried different procedures but none of them are useful,
for(i in 1:nrow(df2)){
for(j in 1:nrow(df1)){
if(df2$v1[i] == df1$v2[j]... |
H: Can I use euclidean distance for Latent Dirichlet Allocation document similarity?
I have a Latent Dirichlet Allocation (LDA) model with $K$ topics trained on a corpus with $M$ documents. Due to my hyper parameter configurations, the output topic distributions for each document is heavily distributed on only 3-6 top... |
H: Measure information gain / loss after a data Transformation operation
Suppose that we have a dataset of 2 samples :
[{1,2,0}, {2,0,0}, {3,1,1}, {4,0,1}, {5,1,1}]
(the last element of each row is the class variable)
If we want to reduce the variety of the column "1" we can put all values that are less or equal to... |
H: Weighted sum of word vectors for document similarity
I have trained a word2vec model on a corpus of documents. I then compute the term frequency (the same Tf in TfIDF) of each word in each document, multiply each words Tf by its corresponding word vector (this is the weighted part), and sum each of these weighted v... |
H: Extracting NER from a Spanish language text file
I am trying to extract various Named Entities from a Spanish language text file. I tried using nltk but to no success. I am using Python 2 with nltk 3.x.
AI: I suggest you take a look at the Python library Spacy it has a model for spanish language that includes NER. |
H: Vanishing Gradient in a shallow network
I created an ANN in Python 3. My backpropagation algorithm seems to work up to a point where the gradient becomes very small. I am familiar with the vanishing gradient problem, but I found that it only applies to really deep network; my simple test network is no such network... |
H: GANs (generative adversarial networks) possible for text as well?
Are GANs (generative adversarial networks) good just for images or can they be used for text as well?
Like training a network to generate meaningful text from a summary.
UPD - quotes from the GAN inventor Ian Goodfellow.
GANs have not been applied t... |
H: Kmodes for Mixed Data
Kmodes is for categorical Data. But sometimes I read it somewhere that it is applicable on Mixed Data i.e., Numeric and categorical.
So whats right?
AI: As far as I remember Kmodes is used for Categorical data, even in the documentation I couldn't find anything related to Mixed Data Type, if ... |
H: When to use Linear Regression and When to use Logistic regression - use cases
Linear Regression is used to find the relation between dependent variable and independent variable.
Logistic Regression is used when dependent variable is categorical.
But this doesn't exactly suffice, what use cases you can use either of... |
H: Recombining rare values
I have a column called item_colour which describes the colour of products in my dataset.
There are 85 colours and some of the colours are unique or they represent a small part of the data ( I have 100,000 observations). For example, there is only one "almond" colour or only two "sky blue". ... |
H: What optimization algorithms are used in scikit-learn?
Gradient descent is one of the well-known optimisation algorithms. However, are the regression algorithms in scikit-learn implemented with gradient descent or some other techniques?
AI: There are multiple approaches to optimization in scikit-learn. I will focus... |
H: How is the number of grid cells in YOLO determined?
I'm now learning YOLO but I don't understand how the number of grid cells is determined. Some article like this one uses 13 x 13 while others use 19 x 19 (e.g. Andrew Ng's course in Coursera). It seems that the height and width should always be the same, but how i... |
H: Clustering mixed data
I have 90000 records for customer segmentation consisting of numeric nominal and ordinal variables:
*houselhold_ID* ID for household
*quantity*: integer, number of products bought
*price*: values 1 to 3 with 1 for 0-5, 2 for 5-8 and 3 for 8-10
*product name*: nominal values 1 to 9 represent... |
H: Which process step in KDD or CRISP-DM includes labeling of the data?
KDD and CRISP-DM are both processes to structure your Data Mining procedure. Is data labeling not also a important part of Data Mining?
Data labeling is for example in unsupervised learning the target of the Data Mining process. So if I want to c... |
H: Cost Function for evaluating a Regression Model
There are several "classical" ways to quantify the quality of (any!) regression models such as the RMSE, MSE, explained variance, r2, etc...
These metrics however do not take "costs" into account, for example, for me it is worse to under-predict a value (Real: 0.5, Pr... |
H: Correlation and feature selection
I'm trying to learn from example on the internet. I choose the Iris dataset.
When I checked for correlation, I saw that there was a correlation between 'petal length' and 'petal width'. But when I run RFE to select only 3 features, it took both these 2 features.
So, my question i... |
H: Clustering mixed data: Find optimal number of clusters
What do you say about this plot to find the number of cluster for kmean or kproto for mixed data. Where is the elbow to identify? I would say 5? I have 11 feautures.
AI: The bumps at 8 and 11 are likely just due to random initialization, and if you rerun with a... |
H: Error in f1(x) : argument "b" is missing, with no default
f1 <- function(a,b,c,d,e,f) {
-111.605*a-208.39+(14.882-b)^2+35.29813*c-.001251205/d-1.050695*e+11.63420*f
}
x = matrix(c(1:66), byrow = T, ncol = 6)
f1(x)
An error of the following occurs:
Error in f1(x) : argument "b" is missing, with no default
AI... |
H: accumarray function not working in matlab
I have an 2D array like the one shown below.
35046, 0.17
1963, 0.34
1135, 0.51
405, 0.68
99, 0.85
1, 0.85
15, 1.02
2, 1.02
I tried using accumarray function in matlab on this data to get the results like this below.
35046, 0.17
19... |
H: Irregular Precision-Recall Curve
I'd expect that for a precision-recall curve, precision decreases while recall increases monotonically. I have a plot that is not smooth and looks funny. I used scikit learn the values for plotting the curve. Is the curve below abnormal? If yes, why and how can I correct it consider... |
H: What is the difference between observation and variable?
I have a matrix with size m×n that is built from n number of individuals for person identification. So, n is the number of person and m is the number of feature's value for the person.
It makes me confused about observation and variables. What will I call n a... |
H: What are suitable predictive analytics models for data from multiple sensors?
I am a newbie in the field of AI/ML. I am trying to implement predictive analytics model on the data generated every minute from a device with sensors.
I have two questions:
What are various ML algorithms I can use to predict the number... |
H: Difference usage of document level, sentence level and aspect level in sentiment analysis
I'm studying about Sentiment analysis. What is the purpose of using Document Level, Sentence Level and Aspect Level?
I read this definition in Web Data Mining book by Bing liu.
In this book it was stated that,
Sentence Leve... |
H: Extract key phrases from a single document
I need to extract relevant key phrases from a single document. Since I don't have a lot of documents, TF-IDF doesn't really work.
Currently I'm using TextRank. It produces okay-ish result - some really good phrases along with a lot of garbage.
Is there a better algorithm ... |
H: How to deal with large data sets
So i'm very new to this, forgive my silly questions.
I've got some data I need to analyse, I would usually just use excel it doesnt seem to be able to do the job.
I have .csv files containing data for every seconds over a year period.
The data consists simlpy of timestamp and valu... |
H: How to transpose rows into single column based on time-stamp index in python?
Sample input dataset is:
Sample output dataset what i want:
0 2017-11-17 10:23:28.691 788
0 2017-11-17 10:23:28.691 756
0 2017-11-17 10:23:28.691 789
0 2017-11-17 10:23:28.691 780
1 2017-11-17 10:23:29.731 788
1 2017-11-17 10... |
H: Strange behavior with Adam optimizer when training for too long
I'm trying to train a single perceptron (1000 input units, 1 output, no hidden layers) on 64 randomly generated data points. I'm using Pytorch using the Adam optimizer:
import torch
from torch.autograd import Variable
torch.manual_seed(545345)
N, D_in... |
H: Do you know a dataset for regression where deep learning outperforms svm and random forests?
I am currently trying to learn about deep learning. I asked myself where deep learning outperforms SVM and Random Forest on regression?
Do you have any dataset for regression where deep learning outperforms SVM and Random F... |
H: The best w_j confusion in xgboost
from XGBoost tutorial, it described:
In this equation $w_j$ are independent with respect to each other, the form $G_j w_j + \frac{1}{2}(H_j+λ)w_j^2$ is quadratic and the best $w_j$ for a given structure $q(x)$
and the best objective reduction we can get is:
$w^∗_j = \frac{−G_j}{H_... |
H: Error in FUN(newX[, i], ...) : argument "Iclo" is missing, with no default
pmv1=function(H,pa,Ta,fcl,Tr,Iclo,M){
Tcl = (35.7 - 0.0275*H + 0.155*Iclo* (H - 0.31*(57.4 - 0.07*H - pa) -
0.42*(H - 58) - 0.0017*M*(58.7 - pa) - 0.0014*M*(34 - Ta)))
hc=(2.4*(Tcl - Ta))
dT= (Tr - 22)
PMV= (4 + (0.303 *exp(-.0... |
H: What are some popular process models for solving problems utilizing?
What are some standard process models which people or companies use to solve their problems utilizing data? I'm familiar with current process models such as CRISP-DM and SEMMA, but I wondered if there are any other approaches or guidelines?
AI: As... |
H: How can I create a space in IBM Cloud?
I want to try the IBM speech to text API. I created an IBM cloud account and went to https://console.bluemix.net/catalog/services/speech-to-text. I see the error message:
Please create a space in the selected org or choose another org.
Where can I create such a space? I wasn... |
H: What is the difference between Linear SVM and SVM with linear kernel?
I'm wondering whether there is a difference between Linear SVM and SVM with a linear kernel. Or is a linear SVM just a SVM with a linear kernel?
If so, what is the difference between the two variables linear_svm and linear_kernel in the following... |
H: How can l get 50 % examples in training set and 50% in test set for each class when splitting data?
l have a dataset of 200 examples with 10 classes. l would like to split the dataset into training set 50% and test set 50%.
for each class, l have 20 examples. Hence, l would like to get for each class : 10 training ... |
H: How to update bias in CNN?
How do we find the gradient and the back propagation error if we had a bias which just added a scalar value after the convolution calculation?
AI: Like the update rule for bias terms in dense layers, in convolutional nets the bias gradient is calculated using the sum of derivatives of Z t... |
H: What is the difference between 8 filters twice and one 16 filters in convolutional layers at CNN?
Why would we use two convolution layers in a row with same spec? E.g. in VGG16 first two layers, they used 3 x 3 filter with 64 depth twice. What is the difference if we use 3 x 3 filter with 128 depth once.
AI: Each ... |
H: What is the efficient way to generate a similarity score when comparing two face images?
I am working on a face recognition application using deep learning. To plot the ROC curves and do performance evaluation, I extracted the features from the last layer of the deep neural network and I have tried Euclidian and Ma... |
H: Why an eigenvector might be reasonable notion of centrality
Using adjacency matrix to represent a connection between node i and node j, 1 means connected and 0 means not connected.
Using eigenvector to represent the centrality means the more nodes with high centrality values a node is connected to, the higher that ... |
H: XGBoost Predictions
I am working on a multi-class classification task for 24 classes using XGBoost. I am training the model as follows:
param = {'max_depth': max_depth, 'eta': learning_rate, 'silent': 1, 'objective': 'multi:softmax', 'num_class': 24}
bst = xgb.train(param, dtrain, num_round)
bst = xgb.Booster({'nth... |
H: Function Callers Vs Data Scientists
In our organization, there are many people who are into analytics and data science who are OK in their work with in the sense that they know what packages in R/Python etc to use, what algorithms to call for a particular type of problem etc. The problem is that they have very litt... |
H: What is the difference between fully observed and partially observed state features in Reinforcement learning ?
When we use a function to approximate Q values or policy to state-action pairs we hear the above two terms fully and partially observed features. what is the difference . Normally in Atari Games they gene... |
H: Multi-class classification metrics in R and Python
I would like to ask if there is a metric in R and Python that serves not only for binary classification. I've found Matthews Correlation Coefficient works well in Python, but in R is only a binary version. Of course, I'm talking about "real" not just binary metrics... |
H: RNN unable to classify time series
I have 400 time series of length 50.
200 of them have values between 1-10 and are considered of type A.
The rest 200 have values 1-10 with the exception that 3 from the total of 50 data points have value 20, and are considered of type B.
I am trying to use a RNN network to make it... |
H: In a recommender system, how can you normalise the similarity between two arbitrary users?
Consider the following problem:
There are 1000 users, 100 items (movies, for example), and 10000 ratings. The probability of a user, $u$, rating a movie, $i$, is $\mathbb{P}(R_{u_i}=\text{yes})=\frac{1}{10}$, and the probabil... |
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