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H: What's the best strategy to train a CNN with images that only have labels for positive characteristics?
I have a large database of images that are only partially labeled for multiple, non-exclusive characteristics or objects present on them. For instance, an underwater scene might feature the labels water, swimsuit... |
H: Q-learning why do we subtract the Q(s, a) term during update?
I can't understand the meaning of $-Q(s_t, a_t)$ term in the Q-learning algorithm, and can't find explanation to it either.
Everything else makes sence. The q-learning algorithm is an off-policy algorithm, unlike SARSA. The Bellman equation describes q-l... |
H: What to give as predictors to predict future values?
I am new to machine learning techniques. I was going through few supervised machine learning model examples and i have doubt in predicting future values.
I have daily time series dataset from database where my target variable is complete noise signal like this:
... |
H: Handle Unbalanced data
I have a data-set with 2 target classes.
In training dataset, the ratio of the 2 classes are 1:93
With my neural network, the current accuracy is 63%.
I tried undersampling, oversampling, equal sampling but not improvements.
AI: You have not specified that what neural network you are using bu... |
H: Several fundamental questions about CNN
I am trying to make a CNN for 3D image recognition but everything is predicted to only one class out of three. And the prediction even quickly converges during the first epoch. I have been working on this for an week and totally lost.
I have my own several guess why it alwa... |
H: XGBoost: predictive, descriptive (or both) model?
I have trained an XGBoost model for prediction. The algorithm is able to calculate variable importances. I was asked why I have not analyzed these variable importances and I did not because as I understood XGBoost is rather a predictive than a descriptive model. I ... |
H: StratifiedKFold: ValueError: Supported target types are: ('binary', 'multiclass'). Got 'multilabel-indicator' instead
Working with Sklearn stratified kfold split, and when I attempt to split using multi-class, I received on error (see below). When I tried and split using binary, it works no problem.
num_classes = l... |
H: Putting a predictive model into production
Even after all these years of data science from 2010 to 2018, why is there no general framework for putting a predictive model into production?
AI: Depending on what exactly you mean by framework, I would argue that there is. Using a REST interface to serve a production mo... |
H: Creating data model out of .csv file using Python
I want to create a data model out of a .csv file using Python. I mean to create dependencies, for example the primary key and stuff such that I can check if the new .csv complies with the given data model. I would appreciate some suggestions regarding how to do that... |
H: Adapting the Keras variational autoencoder for denoising images
I am asking this question here after it went unanswered in Stack Overflow.
I'm trying to adapt the Keras example for VAE
I have modified the code to use noisy mnist images as the input of the autoencoder and the original, noiseless mnist images as the ... |
H: Layer notation for convolutional neural networks
When reading about convolutional neural networks (CNNs), I often come across a special notation used in the community and in scientific papers, describing the architecture of the network in terms of layers. However, I was not able to find a paper or resource describi... |
H: Math behind L2 Regularization for Logistic Regression
I read that L2 regularization in logistic regression creates a sort of sphere that limits the choice of $w$ weight, but why does this happen?
AI: Your question is really about the method of Lagrange multipliers in constrained optimization, not logistic regressio... |
H: Derivation of the cross-entropy equation in Michael Nielsen's book
I am reading the book http://neuralnetworksanddeeplearning.com/chap3.html by Michael Nielsen.
So this is a question mostly for the people familiar with the book and understanding the material.
In the equations (71-75) we are trying to find a cost-fu... |
H: TensorFlow: number of channels of conv1d filter
I want to apply a ConvNet on my one dimensional data retrieved from 13 sensors. So, each of my samples consists of 13 channels (of 51 values)
I am using 'conv1d' to apply a ConvNet on my data. The network works nicely, but I wonder how 'conv1d' determines the number o... |
H: Does it make sense to parallelize machine learning algorithms as part of PhD research?
I'm developing machine learning algorithms to aid in the diagnosis and prognosis of various cancers for my PhD. My lab is an Nvidia teaching center (CUDA).
My supervisor thinks that I need to also optimize ML by parallelizing it... |
H: ANN applied to Boston Housing dataset returns negative value
This example is taken from the book Deep Learning With Python from Jason Brownlee. It applies a fully connected neural model with one hidden layer (13, 13, 1) using Keras library and the Tensorflow backend.
1 - Import the packages
import numpy
from kera... |
H: Get number of correct predictions for each class in Keras
I am having unbalanced dataset(1:93) and want to use kappa's metric.
However, for that I need to capture how many correct predictions are made for each class.
I have tried understanding from here and other google links.
Is it possible to capture class wise #... |
H: Recreating the sum symbol using python
I am currently reading a white paper relating to Expectation-Maximisation (EM) and would like to encode a formula so I can play with it in order to help my understanding. The formula in question is a sum over values and shown below;
I am wondering what the advice on the best ... |
H: How to classify parametric curves?
I am working on a project which aims at determining whether a patient has cervical issues or not, based on a certain movement (for instance, turning the head from left to right and so on).
For each patient, I have one or more sets of coordinates acquired with a VR headset. One pro... |
H: ValueError: operands could not be broadcast together with shapes while using two sample independent t test
I am trying to perform two sample t test. My data set consists of 744 rows and 186 columns for which I have calculated total sum and mean. I need to perform two sample t test. My csv looks like this from which... |
H: Clustering: How to cluster multiple CSV files that each represent a Steam user
I am currently about to do clustering analysis regarding Steam users activity. So I have a thousands of CSV’s, each representing a Steam user and his/her purchased games (with ID and genre). I am planning to use k-modes clustering becaus... |
H: How to train data by batch from disk?
I am working on a convolutional neural network for image classification. The training dataset is too large to be loaded on my computer memory (4gb), on top of that I also need to try some augmentation to balance the classes.
I am using keras. I have looked into many examples bu... |
H: How to import image data into python for keras?
I'm new to CNNs, starting off with keras. I'm currently using ImageDataGenerator to import my train/validation folders (which each have 2 class subfolders for my binary classification task). Was wondering how can I import my train/validation files without using ImageD... |
H: Xgboost interpretation: shouldn't cover, frequency, and gain be similar?
I was surprised to see the results of my feature importance table from my xgboost model. Based on the tutorials that I've seen online, gain/cover/frequency seems to be somewhat similar (as I would expect because if a variable improves accuracy... |
H: Visualizing item similarities
I have an implicit dataset. It contains which user click which item. I'm doing collaborative filtering and finally i get the item similarites. So now i have data like;
Item - SimilarItem - SimilarityValue
A - C - 0.12
A - R - 0.42
A - Y - 0.34
A ... |
H: What does it mean when we say most of the points in a hypercube are at the boundary?
If I have a 50 dimensional hypercube. And I define it's boundary by $0<x_j<0.05$ or $0.95<x_j<1$ where $x_j$ is dimension of the hypercube. Then calculating the proportion of points on the boundary of the hypercube will be $0.995$.... |
H: Can i use deep learning in my agriculture PHD?
My PHD is about yield of soybeans and it is typical agriculture theme, but I am pretty good with programming and Python programming language and I have already some deep learning programs which I made by myself successfully. Problem is that model is not very easy to sh... |
H: Possible to correct an actual cell state in LSTM via gradient?
Why in LSTM we calculate gradient w.r.t weights, but not w.r.t the cell state?
Is it theoretically possible to correct the contents of the cell state, and what would it result in?
I understand that weights are like a "set of skills", so that network can... |
H: When are weights updated in CNN?
In CNNs when do we update the kernel parameters using back propagation? Suppose I have batch size of 50 and training data of 1000. Do I back propagate after each batch has been presented to network or after each data sample?
AI: Whenever you train the network using batch means that ... |
H: Multi-image superresolution using CNNs
I'm trying to write a program that can take multiple low-resolution images as inputs and output a high-resolution image.
My understanding is that for single-image superresolution, Convolutional Neural Networks work great. I can just take a network with just three convolution l... |
H: How does sklearn KNeighborsClassifier compute class probabilites?
The KNeighborsClassifier has a method for predicting class probabilities. However, I cannot find any documentation describing how these probabilities are computed.
Here is a toy example that returns class probabilites:
from sklearn.neighbors import K... |
H: Right Way to Input Text Data in Keras Auto Encoder
I have several thousand text documents and I am currently working on obtaining the latent feature representations of words and generate sentences using variational auto encoder. The main obstacle I am facing is “how to input such large textual vectors into VAE (or ... |
H: Parameter tuning for machine learning algorithms
When it comes to the topic of tuning parameters, most of the time you read grid search. But if you have 6 parameters, for which you want to test 10 variants, you get to 10^6 = 1000000 runs. Which in my case would be several months of processing time.
That's why I was... |
H: compare two lists
I have a SQL (MS SQL Server) database of ~30 million companies. For example:
+-----------------------+----------------+-----------+
| company_name | country | ID_number |
+-----------------------+----------------+-----------+
| Mercedes Benz Limited | Germany | 12345 |
|... |
H: Basic Time Series Classification Examples
I've been using matlab until now to classify a large number of labelled time series I have. This has been relatively successful but I'd like to try using Tensorflow to apply a Deep Learning paradigm instead.
I'm a complete noob at this and so I'm a bit overwhelmed with the ... |
H: Neural Network with Connections to all forward layers
In classical neural nets, we have that each layer is connected only with the following layer. What if we relaxed this constraint and allowed it to be connected to any or all subsequent layers? Has this architecture been explored? It seems to be backprop would... |
H: K-Means vs hierarchical clustering
When hierarchical clustering is preferred over k means clustering?
AI: I would say hierarchical clustering is usually preferable, as it is both more flexible and has fewer hidden assumptions about the distribution of the underlying data.
With k-Means clustering, you need to have... |
H: How were auto encoders used to intialize deep neural networks?
In a document on deep learning about auto encoders, it is said that these networks were used back from 2006 to 2010 for deep neural networks initialization.
Can somebody explain how this was done?
AI: There were a few different techniques. One popular o... |
H: Training Neural network classifier using string inputs
My thesis topic is about building a (deep) neural-network classifier to classify the type of a place. I am given both labels and some inputs in string type. So for example the label "Supermarket" might have a feature like "Food".
How should I feed my string in... |
H: Is there an R build tool like Maven?
Is there an R build tool (like Maven or Gradle for Java) to get the dependencies and package an R project?
AI: The packrat package is what you're looking for.
It bypasses R's native packages and allows you to build and deploy a bundle of packages and dependencies.
However, it do... |
H: Keras LSTM with 1D time series
I'm learning how to use Keras and I've had reasonable success with my labelled dataset using the examples on Chollet's Deep Learning for Python. The data set is ~1000 Time Series with length 3125 with 3 potential classes.
I'd like to go beyond the basic Dense layers which give me abou... |
H: Preprocess list data
I got question about preparation data for my ML algorithm.
Raw data has format similar to:
{
"finances": [
{
"assets": 1230.39,
"investments": 3245.39,
"netProfit": 8765.45,
"year": 2017
},
{
"assets": 111.11,
"investments": 222.22,
"netPr... |
H: Can PCA be applied to reduce dimensionality of only a subset of features?
Lets say I have a feature set of f0 to f1000. I am thinking of applying PCA on f500 to f1000 reducing their dimensionality. Can I combine this reduced set with the features f0 to f499 as the feature space for training a learning algorithm?
AI... |
H: Decision trees for Rstudio v3.3
Anyone know the best packages to build a decision tree in Rstudio v3.3?
I want to look at some data-driven segmentation for my data. I was thinking of doing chaid analysis (mainly because this is why I've done in the past).
I've looked around myself, but can't find the best package ... |
H: Can the number of epochs influence overfitting?
I am using a convolution neural network ,CNN. At a specific epoch, I only save the best CNN model weights based on improved validation accuracy over previous epochs.
Does increasing the number of epochs also increase over-fitting for CNNs and deep learning in general?... |
H: Decision tree not using all features from training dataset
I have built CART model using sklearn. I'm having total 6 features in training dataset and passing all of them in fit function. I've tested both criteria Gini and entropy. But whenever I plot tree using graphviz, the tree uses only 3 features in case of Gin... |
H: Multi-dimentional and multivariate Time-Series forecast (RNN/LSTM) Keras
I have been trying to understand how to represent and shape data to make a multidimentional and multivariate time series forecast using Keras (or TensorFlow) but I am still very unclear after reading many blog posts/tutorials/documentation abo... |
H: Why does GridSearchCV (sklearn) change the value of n_samples?
I thought n_samples is the number of training examples. But when using GridSearchCV, n_samples becomes 32 rather than 50.
Error when using GridSearchCV:
Expected n_neighbors <= n_samples, but n_samples = 32, n_neighbors =
50
Training examples:
prin... |
H: Unable to Use The K-Fold Validation Sklearn Python
I have an dataset.
I am unable to use the K-Fold Validation. I am getting the error raised:
ValueError("{0} is not supported".format(y_type))
ValueError: continuous is not supported .
I do not want to do encoding to int, since it may affect the data, and also I w... |
H: Feature importance parameter in machine learning models like Naive Bayes
Sorry for vague heading for the question. My question is that, is there any way to compare features (or attributes) used in machine learning algorithm? I have used Naive Bayesian classifier for binary classification which consists of total 6 f... |
H: Is a 100% model accuracy on out-of-sample data overfitting?
I have just completed the machine learning for R course on cognitiveclass.ai and have begun experimenting with randomforests.
I have made a model by using the "randomForest" library in R. The model classifies by two classes, good, and bad.
I know that when... |
H: Tips & Tricks on training DCGAN on small dataset
I have made a DCGAN which I am trying to train on custom dataset of only 1200 images. I have tried to gather more, but even gathering these 1200 was hard enough. If you are wondering I used Google Chromes extension "Fakun Batch Download Image" to gather my dataset.
T... |
H: What is the allowable limit of oversampling?
Suppose I have 2 classes. One class has 16 samples and the other class has 435 samples. Is it justified to oversample the class with 16 sample to have a 435 number of samples? Or is it better to undersample the class with 435 samples? If so, what should be the number of ... |
H: Should we apply normalization to test data as well?
I am doing a project on an author identification problem. I applied the tf-idf normalization to train data and then trained an SVM on that data.
Now when using the classifier, should I normalize test data as well. I feel that the basic aim of normalization is to m... |
H: Multi-class classification v.s. Binary classification
A training set has five classes including:
"label-A", "label-B", "label-C", "label-D", "others"
But the problem is much simpler - it is to determine whether each input belongs to "label-ABCD" or "others". In this case, there are two solutions to solve this prob... |
H: Random Forest Multiclass Classification
Problem Statement:
Given the details about a product, we need to map it to its category.
Currently we are using Product Name as a feature and Product Category as the Label
There are around 50,000 categories available currently and it will grow in future.
I created a small d... |
H: Meaning of "TRUE" column in R RandomForest output for Importance()?
I want to assess the importance of variables in my model using the Importance() function of R RandomForest package. I have a binary response variable / class and binary feature values.
mytree.rf <- randomForest(class ~ ., data=mydata, ntree=1500,ke... |
H: Are there any examples of neural networks that take two samples as input with a label of {same class, different class}?
There must be examples of this, though I haven't been able to find any. Maybe I don't know what to search for.
AI: Yes. This is how a face recognition algorithm might work for example, where two p... |
H: What Is Saturating Gradient Problem
Can anyone explain what is Saturating Gradient problem? It would be nice if anyone can provide math details as well. Thank you in advance!
AI: If you use sigmoid-like activation functions, like sigmoid and tanh, after some epochs of training, the linear part of each neuron will h... |
H: Best practice for developing using Spark
I am looking for any tips and best practice on how to develop applications using Spark. I currently have access to a cluster, with data as well as a version of Spark 2.1.0 on an edge node and IntelliJ on my local machine.
I am wondering what the best way would be to go about... |
H: Is there a person class in ImageNet? Are there any classes related to humans?
If I look at one of the many sources for the Imagenet classes on the Internet I cannot find a single class related to human beings (and no, harvestman is not someone who harvests, but it's what I knew as a daddy longlegs, a kind of spider... |
H: How to match up categorical labels in training and evaluation
I am creating a CNN to categorise a sentence into one of N possible labels.
I have used the tutorial from WildML to start the code, and I have modified it to allow multiple outputs instead of just true/false.
I am using VocabularyProcessor to convert th... |
H: Is there a thumb-rule for designing neural-networks?
I know that a neural-network architecture is mostly based on the problem itself and the types of input/output, but still - there's always a "square one" when starting to build one. So my question is - given a input dataset of MxN (M is the number of records, N i... |
H: How to choose variables for regression
I have a dataset of long/short equity hedge funds returns and their associated benchmarks (market indices).
I need to form multiple regression on the fund returns using the benchmarks returns as independent variables (i am allowed to form linear combination or manipulation of... |
H: Calculating correlation of slightly out of sync data
I am trying to do some analysis on some data that comes from special glasses that track a few things including pupil size and gaze velocity. I would like to calculate the correlation between two glasses on two different people. At the moment I cannot use df.corr... |
H: Including the dependent variable in your data to perform principal component analysis?
Let's say you have a data set with GPA (dependent variable) and Amount of alcohol, Amount of study, IQ, and SAT score as the independent variables. And you want to perform the principal component analysis in R for dimension reduc... |
H: Kernel with complex vectors
I have a question regarding my machine learning lecture where we had to decide whether $$K(x,y)=x_1y_1-x_2y_2$$ is a valid kernel (e.g. for a SVM). My intuition would say that it is a valid kernel since we can display it with: $$\Phi(x)=(x_1, ix_2)\implies K(x,y)=\Phi(x)\Phi(y)$$ with $i... |
H: Machine Learning to predict risk of items
I'm trying to find out what I need to research and start learning to try and apply machine learning to this problem:
In multiple offices I have 20 chairs, all of these chairs will need to have a risk assessment carried out, as the chairs become older I want to understand w... |
H: Looking for advice: data transfer
I'm requesting data from a government body, and they asked me what format I want to receive the data in. This will be a table of about 400,000 rows and about 10 columns. My options are:
"comma or tab delimited ASCII, Microsoft Access database, Microsoft Excel file etc"
They also wa... |
H: Linear Regression of Sine wave using Gradient descent Not working
I am writing an algorithm to fit a sine wave. I want to have 4 parameters ( amplitude, frequency, phase & centre position). When I tried to program with all 4 parameters I wasn't able to find a good fit. So I tried to first make it work with each par... |
H: How to build a recurrent neural net in Keras where each input goes through a layer first?
I'm trying to build an neural net in Keras that would look like this:
Where $x_1$, $x_2$, ... are input vectors that undergo the same transformation $f$. $f$ is itself a layer whose parameters must be learned. The sequence le... |
H: Imbalanced data causing mis-classification on multiclass dataset
I am working on text classification where I have 39 categories/classes and 8.5 million records. (In future data and categories will increase).
Structure or format of my data is as follows.
--------------------------------------------------------------... |
H: Normalizing the final weights vector in the upper bound on the Perceptron's convergence
The convergence of the "simple" perceptron says that:
$$k\leqslant \left ( \frac{R\left \| \bar{\theta} \right \|}{\gamma } \right )^{2}$$
where $k$ is the number of iterations (in which the weights are updated), $R$ is the maxi... |
H: Is the gradient descent the same if cost function has interaction?
We know how to determine regression parameters using gradient descent. If
and the cost function is C=|Y-Y(X)|^2, we update b as
where is the learning rate and is the partial differential of the cost function C with respect to b.
If in multiple... |
H: What is the use of additional column of 1s in normal equation?
Currently I am going through Normal Equation in Machine Learning.
$$
\hat\theta = (X^T \cdot X)^{-1} \cdot X^T \cdot y
$$
But when I see how they use this equation, I found they always add an additional column of 1s in the starting of matrix X before t... |
H: Improve Precision of a binary classifier - Decision Tree in Python
Currently, I am working on a project. The dataset is balanced roughly in the ratio of 50:50. I created a decision tree classifier. I am achieving decent accuracy (~75%) on validation data but the precision for the target variable is biased. For clas... |
H: How to build an encoder using a distance matrix
I have a similarity/distance matrix:
a | b | c
a 0 | 1 | 2
b 1 | 0 | 3
c 2 | 3 | 0
I want to build an encoder/model that learns an n-dimensional representation of each of the points in the dataset s.t. the euclidean-difference between the representations produc... |
H: Perceptron learning rate irrelevant in convergence
Via this MIT document i studied the single layer Perceptron convergence proof (= maximum number of steps).
In the convergence proof inside this document , the learning rate is implicitly defined as 1 .
After studying it, by myself i tried to re-do the proof inserti... |
H: Non Deterministc Dimensionality reduction
could you please suggest me a nondeterministic algorithm for dimensionality reduction except t-SNE.
AI: Autoencoders are non-deterministic, since they rely on a random weight initialization. |
H: How to download dynamic files created during work on Google Colab?
I have two different files and on the first, I tried to save data to file as:
np.save(open(Q1_TRAINING_DATA_FILE, 'wb'), q1_data)
On second file, i'm trying to load it the same way using:
q1_data = np.load(open(Q1_TRAINING_DATA_FILE, 'rb'))
I then... |
H: What are examples for XOR, parity and multiplexer problems in decision tree learning?
In scikit-learn documentation and in decision tree learning Wikipedia article there is mention of "There are concepts that are hard to learn because decision trees do not express them easily, such as XOR, parity or multiplexer pro... |
H: How the "def match(self, example)" method is automatically calling and how the example arguments is working here?
trainung_data = [
['Green', 3, 'Apple'],
['Yellow', 3, 'Apple'],
['Red', 1, 'Grape'],
['Red', 1, 'Grape'],
['Yellow', 3, 'Lemon'],
]
header = ["color", "diameter", "label"]
def is_nu... |
H: What is the advantage of using Dunn index over other metrics for evaluating clustering algorithm?
There are many metrics to evaluate clustering algorithm like Calinski-Harabaz Index, Dunn index, Rand index, etc. Are there any advantage of using Dunn index over other metrics for evaluating clustering algorithm (K-me... |
H: Applying dimensionality reduction on OneHotEncoded array
I have a really large data set with mixed variables. I have converted categorical variables to numerical using OneHotEncoding and it has resulted in more than a couple of thousand different features, combined that is.
Is it possible to apply dimensionality r... |
H: Why do we need to discard one dummy variable?
I have learned that, for creating a regression model, we have to take care of categorical variables by converting them into dummy variables. As an example, if, in our data set, there is a variable like location:
Location
----------
Californian
NY
Florida
We have to c... |
H: Help me understand how word-as-vector representations are constructed
Let's suppose I have a big list of words. I want to turn this list into a vector space of dimension $N$ such that each word is a vector in this vector space. But I have no idea how to go about with that. Some questions:
Is the list enough? For e... |
H: Orange: Data has no target variable error
I am trying to apply Random Forest algorithm on a data set using Orange. The target variable is not set in the data set. However, I know which column is the target variable.
How can I specify the target variable in a .csv file using Orange or any other tools?
AI: You can sp... |
H: Guided topic modeling: generating words from topics
I need to generate lists of words related to specific topics for a project. I am familiar with clustering methods of topic modeling such as LDA, but I have something else in mind. Are there any methods to generate lists of related words from a root word? For insta... |
H: Does Tensorflow support a Decision Tree Classifier?
I am trying to implement decision tree classifier to classify my data set. I am using Python. Now it is easy to implement in scikit learn, but how can I implement this in tensorflow.
AI: Basically I guess TensorFlow does not support decision trees. I quote from he... |
H: How to approach model reporting task
I have been tasked to report on an ensemble model that was created in h2o which includes several model subtypes such as Random Forest, GBM, linear models etc. The end goal is to predict churn rates for products in a large telco company, but the approach we use could apply to an... |
H: Classification or regression? Which model is more accurate if I only care about being above or under the threshold?
If I have a regression problem that can also be a classification problem by converting a continuous variable to a binary depending on a threshold, which model would be more accurate if I only care abo... |
H: Class weight degrades Multi Label Classification Performance
I noticed something strange while I was conducting a multiple label classification problem via keras neural network. My data set consist of imbalance data with 12 features and 25 possible labels. When I instantiate my model with no class weight I get a pr... |
H: interpret results of nvidia-smi
Every 1.0s: nvidia-smi Tue Feb 20 12:49:34 2018
Tue Feb 20 12:49:34 2018
+--------------------------------------------------... |
H: Is R2 score a reasonable regression measure on huge datasets?
I'm running a regression model on a pretty large data set and getting a fairly woeful $R^2$ score of ~0.2 (see plot below), despite the plot looking like the model is generally pointing in the right direction.
My question is, when you have over a million... |
H: k-means with one cluster
K-means may give different results, because the initial choice of centroids is random.
However, if I were to choose k=1, will the algorithm always provide the same answer equal to the "barycentre" of my data?
AI: Yes. The centroid will converge to the center of all your data and this will ... |
H: Is a good practice to sum each rate (i.e. crime rate per 100.000 people)?
Consider a dataset from 1990 to 2017 that contains the crime rate per 100,000 people in some cities from Latin America.
I want to measure which city is more complex according to this data and other indicators. I'm using The analytic hierarchy... |
H: Get a portion of a long field in Pandas?
I have a Pandas dataframe that has some fields that contain very verbose text. I want to be able to iterate through the DF but only display a limited set of words. I have code similar to:
for index, row in df.iterrows() :
print(row['A'], row['B'])
How can I make sure th... |
H: How do I arrange my data to predict 6 weeks of daily sales
I have a data.table base that has many variables to use them to forecasting sales for the next 6 weeks of daily sales. In fact, all the database is arranged by date as you can see here.Note that here I just show you some of variables.
> Data_train[order(Dat... |
H: How to obtain with a RRN a version of a temporal XOR function using keras/tensorflow?
I'm trying to implement a model of a recurrent neural network to solve a temporal version of the XOR problem, but I am not still able to do that. Any hints?
AI: I think following this link helps you, I have gone trough those tutor... |
H: Is There any RNN method used for Object detection
after reading the state of the art about object detection using CNN (R-CNN Faster R-CNN ,YOLO, SSD...) I was wondering if there is a method that use RNN's or that combine the use of CNN's and RNN's for object detection ??
Thank you
AI: Yes, there have been many atte... |
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