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H: Convert date into number - Apache PIG
Imagine that I've a field called date in this format: "yyyy-mm-dd" and I want to convert to number like "yyymmdd". For that I'm trying to use this:
Data_ID = FOREACH File GENERATE CONCAT((chararray)SUBSTRING(Date,0,4),(chararray)SUBSTRING(Date,6,2),(chararray)SUBSTRING(Date,9,2... |
H: value saveAsTextFile is not a member of org.apache.spark.sql.DataFrame
How Can I save a DataFrame as a CSV in HDFS?
I'm trying with this:
df.groupBy("Product_ID").agg(collect_list($"Stock")).saveAsTextFile("PATH/results.csv")
AI: This is not standard part of the API of DataFrames. You can either map it to a RDD, jo... |
H: What does Negative Log Likelihood mean?
I have a data set which has continuous independent variables and a continuous dependent variable. To predict the dependent variable using the independent variables, I've run an ensemble of regression models and tried to compare them against each other. Here are the results fo... |
H: Do I need a strong programming background to become a data analyst?
I'm thinking about becoming a data analyst, and I'm wondering if programming knowledge is a must for this. I'm fairly strong with maths, but I have very little programming experience. Do all data analysts have strong programming skills (R, SAS, SQL... |
H: Does dropout require multiple passes of the same data set, as a sort of ensemble method?
I'm a bit confused about dropout -- on one tutorial, it was described as basically an 'ensemble method' of sorts. This implies that you might need to create an ensemble of networks. Is this the case, where you would need to get... |
H: I need to measure Performance : AUC for this code of NLTK and skLearn
The code below measures precision and recall and F-measure (source). How can I measure AUC?
import collections
import nltk.metrics
from nltk.classify import NaiveBayesClassifier
from nltk.corpus import movie_reviews
def word_feats(words):
re... |
H: What do this Classification evaluation results mean to you? Do they are suspicious or not?
I have collected dataset with two class labels and used the SVM Method to classify the dataset, and this is the results. Does this appear suspicious or not?
scikit-learn classifiers with SVM SVC train on 114859 instances, te... |
H: Word vectors as input
I have a corpus on which I want to perform sentiment analysis using LSTM and word embeddings. I have converted the words in the documents to word vectors using Word2Vec. My question is how to input these word vectors as input to Keras? I don't want to use the embeddings provided by Keras.
AI: ... |
H: Machine Learning Best Practices for Big Dataset
I am about to graduate from my Master and had learnt about machine learning as well as performed research projects with it. I wonder about the best practices in the industry when performing machine learning tasks with Big Datasets (like 100s GB or TB). Appreciate if f... |
H: Getting uniform distribution over topics from gensim's LDA?
I am trying to learn topics distribution for each document in a corpus.
I have term-document matrix (sparse matrix of dim: num_terms * no_docs) as input to the LDA model (with num_topics=100) and when I try to infer vectors for each document I am getting ... |
H: Features of word vectors in Word2Vec
I am trying to do sentiment analysis. In order to convert the words to word vectors, I am using Word2Vec model. Suppose I have all the sentences in a list named 'sentences' and I am passing these sentences to word2vec as follows:
model = word2vec.Word2Vec(sentences, workers=4 , ... |
H: Classifier on top of LDA topic vectors?
I have training data in form of pair of documents with an associated label - {doc1, doc2, label}. Label is defined as function of pair of documents.
Now I want to build a model which can predict the label given two new documents.
I want to try different representation of doc... |
H: Network Analysis using R
I've the following dataset:
**Strenght Movie1 Movie2**
23 2 3
80 1 2
10 4 3
And I want to create a graph with the relationships between movies having the first column as the strenght of the relationship. How can I do this ... |
H: Do categorical features always need to be encoded?
I'm using Spark's Machine Learning Library, and features are categorical. The features are strings, and Spark's MLlib (like many other machine learning libraries) does not accept Strings as inputs.
The normal procedure for overcoming this is to convert Strings to i... |
H: Standardization/Normalization test data in R
I understand that one should standardize and normalize the test data (or any "unlabeled" data) with the training mean and sd. How can I implement this in R language? Is there a kind of "fitting" to the training set and a kind of applying to the test data?
AI: Check out t... |
H: Can overfitting occur in Advanced Optimization algorithms?
while taking an online course on machine learning by Andrew Ng on coursera, I came across a topic called overfitting. I know it can occur when gradient descent is used in linear or logistic regression but can it occur when Advanced Optimization algorithms s... |
H: Any guidance for new beginners interested in data science
I am a student with a master degree in biostatistics. I am interested in data science. I know SAS and R. No experience with python. May I ask for your experts' advice on how to teach myself data science from zero, please?
Any advice is much appreciated.
AI: ... |
H: Transformation from Datawarehouse into Big Data structure
What are the required stages for transferring data in datawarehouse into big data structure. Are there any tools and methods that support it?
How to use the schema for such transformation, how to deal with different data types like facts and dimensions for ... |
H: Calculate feature weight vector for one-hot-encoded data frame in R
I have the following data frame with one categorical and two numerical columns:
V1 V2 V3
1 A 1 3
2 A 3 5
3 B 3 3
4 C 2 3
I have turned this into the following dummy variables:
V1.1 V1.2 V1.3 V2 V3
1 1 0 ... |
H: importing csv data in python
I have a csv file with around 130 columns and 6000 rows
what is the best way to import them into python, so that I can later use them in a classification algorithm(columns are the labels and rows are individual samples)
AI: Use pandas library:
import pandas as pd
pd.read_csv('foo.csv'... |
H: What is the purpose of multiple neurons in a hidden layer?
On the surface, this sounds like a pretty stupid question. However, i've spent the day poking around various sources and can't find an answer.
Let me make the question more clear.
Take this classic image:
Clearly, the input layer is a vector with 3 c... |
H: Counting the number of layers in a neural network
I am going over the Udacity tutorial on Neural Networks.
Here's a diagram from the tutorial:
What makes this a '2 layer neural network'?
I was under the impression that the first layer, the actual input, should be considered a layer and included in the count... |
H: How do multiple linear neurons together allow for nonlinearity in a neural network?
As I understand it, the point of architecting multiple layers in a neural network is so that you can have non-linearity represented in your deep network.
For example, this answer says: "To learn non-linear decision boundaries when... |
H: Ordinal feature in decision tree
I am curious if ordinal features are treated differently from categorical features in decision tree, I am interested in both cases where target is categorical or continuous.
If there is a difference, could you anybody point to good source with explanation and any packages (R or Pyth... |
H: Tool to label images for classification
Can anyone recommend a tool to quickly label several hundred images as an input for classification?
I have ~500 microscopy images of cells. I would like to assign categories such as 'healthy', 'dead', 'sick' manually for a training set and save those to a csv file.
Basically,... |
H: sklearn.cross_validation.cross_val_score "cv" parameter question
I was working through a tutorial on the titanic disaster from Kaggle and I'm getting different results depending on the details of how I use cross_validation.cross_val_score.
If I call it like:
scores = cross_validation.cross_val_score(alg, titanic[pr... |
H: Predictive Modeling of Multiple Items
I have a dataset of Social Media Post and want to predict the number of "thumbs up" it will receive over time.
+---------+----------------+-----------+----------------+-----+-------+
| Post_id | Timestamp | Follows | Comments_count | ... | Likes |
+---------+------------... |
H: Imputing missing values by mean by id column in R
This is fairly straight forward but i am unable to do it. My data frame has a id variable which is repeating. For same id I want to replace the NAs in other continuous variable(rating and sur) with their corresponding mean. can anyone pls suggest
ID rating Sur
101 6... |
H: Join two dataframes - Spark Mllib
I've two dataframes. The first have the some details from all the students, and the second have only the students that haved positive grade.
How can I return only the details of the student that have positive grade (make the join) but not using SQL Context.
I've this code:
val all_... |
H: Is there any technique, which can decide no. of bags for Bagged Logistic regression?
In case of Bagged Logistic regression, people suggest more the bags better will be results.
There should be some threshold for more. Is there any technique available which can suggest no. of bags for the type of data available.
Fo... |
H: Is ROC and AUC the only criteria for choosing a model?
If no, what are the other criteria. Please elaborate.
What should be minimum value of AUC to select a model.
AI: Not at all, and AUC is not a particularly well-respected measure of model performance. It performs particularly poorly for rare events, since the u... |
H: Music corpus sentence level clustering
I provide an offline library of Music to my users.
My goal is to understand what my users are looking for, which means translate raw user searches to: Music Artists, Songs, Albums and then add music to the company library.
What are the suggested clustering algorithms to group ... |
H: Score for Ranked plots using scatter plot widget
I'm using orange 3 and when I Score plots using the scatter plot widget how do I view the numerical score associated with the ordered list of plots. Did that feature get removed with the upgrade from 2.7 to 3?
Thanks,
AI: Hm, what was the meaning of this score?
See.... |
H: Do logistic regression and softmax regression do the same thing?
If the both do the same thing then which give us better accuracy?
AI: There is a key difference:
Softmax regression provides class probabilities for mutually exclusive classes.
Logistic regression treats class membership for each class separately. Cl... |
H: Linear regression - LMS with gradient descent vs normal equations
I wonder when to use linear regression with stochastic or batch gradient descent to minimize the cost function vs when to use normal equations? The algorithms using gradient descent are iterative, so they might take more time to run, as opposed to th... |
H: Naive Bayes: Divide by Zero error
OK this is my first time in ML and for starter I am implementing Naive Bayes. I have Cricket(sports) data in which I have to check whether the team will win or lost based on Toss Won|Lost and Bat First|Second. Below is my code:
from sklearn.naive_bayes import GaussianNB
import nump... |
H: Online Variational Autoencoder
when training a VAE, typically one samples from the latent distribution using the reparametrization trick using a fairly large minibatch size (>100) in the decoder/generator half of the VAE. I'm assuming this minibatch size allows the network to 'smooth' out the error and allows us to... |
H: Can I use categorical data and Decision Trees to regress a continuous variable?
Is there a way to take a set of data that consists of discrete values and predict a continuous value? Take for instance data that looks like:
sample matrix of jewel data
color | size | shape
['red' ,'large','square']
['blue','small',... |
H: Pivot DataFrame while calculating new values
I have reduced the data set to only the columns I need:
| yearID | POS | PO | A | E |
|--------|:---:|:--:|:-:|:-:|
| 1871 | SS | 0.0|3.0|1.0|
| 1871 | 2B |30.0|1.0|0.0|
| ... | .. | ...|...|...|
source: Sean Lahmans 2015 Baseball Data set Using the Fielding.c... |
H: What is the difference between model hyperparameters and model parameters?
I have noticed that such terms as model hyperparameter and model parameter have been used interchangeably on the web without prior clarification. I think this is incorrect and needs explanation. Consider a machine learning model, an SVM/NN/N... |
H: Is a neural network suitable for this application
Apologies if this question is not a suitable format. I am a novice in data science.
I have a database of species observation data consisting of ~16 million records.
Each record consists of:
latitude
longitude
date
time
species observed (that's species singular, not... |
H: xgboost speed difference per API
How can it be that a xgboost.cv cross-validation operation where n-folds are evaluated is quicker than a single XGBoostClassifier.fit(X,y) of the xgboost.sklearn API?
AI: I believe this is the answer: https://github.com/dmlc/xgboost/issues/651
the sklearn api uses n_estimators= 100... |
H: What does "zero-meaned vector" mean
I'm trying to reproduce an algorithm designed in a paper. And everything is going well except one thing:
It says we considered the lengths zero-meaned accelerometer vectors and created a feature for the mean and standard deviation of this value. and I do not understand what is it... |
H: How to train neural network that has different kind of layers
If we have MLP then we can easily compute the gradient for each parameters, by computing the gradient recursively begin with the last layer of the network, but suppose I have neural network that consist of different type of layer for instance Input->conv... |
H: Convolution operator yields negative index of matrix
When I read about convolutional neural network from the internet, like this one, mostly I found that discrete convolution operator is defined as follow:
$$C=I*F$$
$$C(x,y)={\sum_{a=0}^{k-1} }{\sum_{b=0}^{k-1}}I(x-a,y-b)F(a,b)$$
Where the size of $F$ is $k\times k... |
H: How to replace NA values with another value in factors in R?
I have a factor variable in my data frame with values where in the original CSV "NA" was intended to mean simply "None", not missing data. Hence I want replace every value in the given column with "None" factor value. I tried this:
DF$col[is.na(DF$col)]... |
H: Cut-Off using Frequent Pattern Mining - Spark Mllib
I am using the Association Rules algorithm using this:
http://spark.apache.org/docs/latest/mllib-frequent-pattern-mining.html
I'm have 83945 transactions in my dataset. And I want to filter some products that only appears X times in my dataset. Basically, I want t... |
H: Approaching data science
I'm totally naive to Data Science - that is, the relatively new, somewhat hyped-field that is so popular at the moment. But I'm not naive to data ... as a scientist and researcher I've worked with all sorts in different roles in the past.
Now I'm in the lamentable position of having dug a l... |
H: Handling a feature containing multiple values
I have a dataset in following format:
Movie ID | Actors | Director | language | ReleaseYear | Genre
1 | Anil Kapoor;Manisha Koirala;Jackie Shroff;Anupam Kher;Danny Denzongpa;Pran | Vidhu Vinod Chopra | hin | 1994 | Drama;Romance;Patriotic
As you can see the c... |
H: Clustering tendency using hopkin's statistics
As per the references
1. http://www.sthda.com/english/wiki/assessing-clustering-tendency-a-vital-issue-unsupervised-machine-learning
2. http://www.listendata.com/2016/01/cluster-analysis-with-r.html
The Hopkins statistics value close to '0' is also clusterable. Is... |
H: Postitive event but unsure when it occurred in time
Morning,
I have a lot of data of which I am positive an event (target data / the event I want to predict going forward) occurred within a two week time frame, however I am unsure when it happened within this time frame.
I can get daily or more frequent feature da... |
H: Difference of Activation Functions in Neural Networks in general
I have studied the activation function types for neural networks. The functions themselves are quite straightforward, but the application difference is not entirely clear.
It's reasonable that one differentiates between logical and linear type functio... |
H: Is a correlation matrix meaningful for a binary classification task?
When examining my dataset with a binary target (y) variable I wonder if a correlation matrix is useful to determine predictive power of each variable.
My predictors (X) contain some numeric and some factor variables.
AI: Well correlation, namely P... |
H: Quick start using python and sklearn kmeans?
I started tinkering with sklearn kmeans last night out of curiosity with the goal of clustering users into groups to see what kind of user groups I can derive. I am lost when it comes to plotting the results as most examples have nice (x,y) coordinates. For example, th... |
H: Benchmarks based on neural networks libraries to compare the performance between different GPUs
I am looking for benchmarks based on neural networks libraries (Theano/TensorFlow/Torch/Caffe/…) to compare the performance between different GPUs.
I am aware of:
https://github.com/jcjohnson/cnn-benchmarks (CNN in Torc... |
H: Sentence similarity
Every week I get a group of sentences (~1000) each of them may be similar. Example:
metallica hard wired
metallica hardwire
metallica hardwired
metallica hard wire
hardwired metallica
hardwire metallica
hardwire
I'm using Cosine similarity to find common documents and group them.
I have realiz... |
H: How are deep-learning NNs different now (2016) from the ones I studied just 4 years ago (2012)?
It is said in Wikipedia and deeplearning4j that Deep-learning NN (DLNN) are NN that have >1 hidden layer.
These kind of NN were standard at university for me, while DLNN are very hyped right now. Been there, done that - ... |
H: Pearson correlation method using absolute values and relative values
I have a dataset with election results and crime rates per city. For each variable I have an absolute value (i.e. Total votes, Total crimes) and a relative value (i.e. Percentage shares of votes).
I want to calculate the correlation coefficient fo... |
H: How to interpret silouette coefficient?
I'm trying to determine number of clusters for k-means using sklearn.metrics.silhouette_score. I have computed it for range(2,50) clusters. How to interpret this? What number of clusters should I choose?
AI: They are all bad. A good Silhouette would be 0.7
Try other clusterin... |
H: Visualizing items frequently purchased together
I have a dataset in following structure inserted in a CSV file:
Banana Water Rice
Rice Water
Bread Banana Juice
Each row indicates a collection of items that were purchased together. For example, the first row denotes that the items Banana, Water, and Rice ... |
H: How to get the probability of belonging to clusters for k-means?
I need to get the probability for each point in my data set. The idea is to compute distance matrix (first column contsins distances to first cluster, second column conteins distances to second cluster and etc). The closest point has probability = 1, ... |
H: Period Predictive Model
I am not sure how to formulate this problem clearly into a machine learning task yet. So hope you guys can chime in and give me some help.
Problem : To predict whether someone will pick up their phone during office hours in week n+2 by looking at customer's behaviour in week n.
Data : I... |
H: Why we use information gain over accuracy as splitting criterion in decision tree?
In decision tree classifier most of the algorithms use Information gain as spiting criterion. We select the feature with maximum information gain to split on.
I think that using accuracy instead of information gain is simpler approac... |
H: Regression in Predicting Tenancy Lengths
I'm currently working on a project involving the prediction of tenancy lengths. I've so far managed to get to a point where I've processed the data and pruned my Random Forest model (via sklearn in Python) to the following accuracy levels (in days):
Train MAE: 131
Train R^2:... |
H: How evaluate text clustering?
What metrics can be used for evaluating text clustering models? I used tf-idf + k-means, tf-idf + hierarchical clustering, doc2vec + k-means (metric is cosine similarity), doc2vec + hierarchical clustering (metric is cosine similarity).
How to decide which model is the best?
AI: Check... |
H: What does Theano dimension ordering mean?
In this code , line 13 is commented as Theano dimension ordering mode. What does this mean?
AI: Let's say you're working with 128x128 pixel RGB images (that's 128x128 pixels with 3 color channels).
When you put such an image into a numpy array you can either store it with a... |
H: Difference between MDS and other manifold learning algorithms
From sklearn docs:
Note that the purpose of the MDS is to find a low-dimensional representation of the data (here 2D) in which the distances respect well the distances in the original high-dimensional space, unlike other manifold-learning algorithms, it... |
H: LSTM input in Keras
I am confused about the input vector in LSTM model, the data I am using is the text data, e.g. 1,000 sentences. I have two questions about the LSTM input layer:
1.If I would tokenize those sentences into the vectors (we can call it sentence vectors), is there a way in Keras to make sentence vect... |
H: Is it possible using tensorflow to create a neural network that maps a certain input to a certain output?
I am currently playing with tensorflow, but can't seem to get a hold whether it usefull for my problem?
I need to create a neural network, that is capable of mapping input to output.
The way things are progres... |
H: Supervised learning with tagged images
I am new to ML and looking to learn with some project. I have a medical imaging dataset where an image (image is a time series of an object so multiple images) has been looked at by radiologist and they have graded it on a scale of 1-5 for some pathology.
Now, I would like to ... |
H: Data that's not missing is called...?
Is there a standard term for data that are not missing? I.e. is it called non-missing, present, or something else?
AI: Depends on content, but I would probably go for "observed" (vs. "unobserved"). A suitable direct antonym of "missing" might be "extant". |
H: Multitask multivariate regression?
I'm trying to solve a multivariate regression problem similar to PLS regression.
The problem can be described as a connectivity analysis problem where we have two regions with unknown unidirectional connections(many-to-many) and given a set of input region patterns and output regi... |
H: Create data visualization for unstructured data - Basket Market Analysis
I have this dataset (just a sample):
product1,product2,product3
product1,product4
product1,product2
product4,product3,product1,product2
The products are grouped by transaction. I want to create some data visualization using this dataset but I... |
H: How to transform an imbalanced attribute to make it more suitable for linear regression?
I'm new to data science but trying to get better
Here I have an attribute and plotting its histogram
From what I know so far such a distribution is imbalanced and my goal is to equalize things a little bit right?
Again from wh... |
H: Feature extraction for sentiment analysis
I am working on a group project for my capstone course and we have been tasked with creating a sentiment analysis tool with Python business logic and (L/W)AMP everything else.
We have good feedback for every part of our project plan except for feature extraction. One of our... |
H: AttributeError: type object 'DataFrame' has no attribute 'read_csv'
I'm trying to create some charts using Python. I've this dataset in a CSV file:
Banana Water Rice
Rice Water
Bread Banana Juice
And I've this code:
import numpy as np
from pandas import DataFrame
import matplotlib
matplotlib.use('agg... |
H: Is there a Hyperopt equivalent for optimization in R?
I've used Hyperopt in Python, but I'm looking for a package with similar capabilities in R. Does a package like this exist?
AI: Give a try to DEoptim(). This package might solve your problem. For the documentation and more information visit-
Documentation
CRAN-... |
H: How to interpolate and check correlation of two time series with differing cardinality
I want to check how correlated two time series are, but they don't have the same cardinality. They have different number of data points because the timestamps the data are collected are different. Available libraries I have found... |
H: How to get the inertia at the begining when using sklearn.cluster.KMeans and MiniBatchKMeans
When I cluster a lot of data, it is hard to run KMeans and wait it stop until centers has not change, so I have to stop KMeans when it reach maximum number of iterations.
Here come problem: how can I evaluate the impact of... |
H: Word2vec - KeyError
I trained a word2vec from the gensim package. Even though I pass a word in the model.train() method, it doesnt appear in the model's vocab.
Can such a case arise?
Why does it happen so?
AI: The reason behind this is the default value for min_count is 5 in word2vec. Since my words have very less... |
H: High dimensional space is dense or sparse?
I read some blog articles recently. One mentions that you could not imagine high dimensional space as 2d or 3d as distance between any 2 points in high dimensional space tends to be similar, which means 'dense'. However in the t-SNE paper, it says high dimensional space te... |
H: How can I detect events on fuel tank
Hi guys.
I'm not a data analyst and I need some direction in this. I'm looking for a way to know the events of the fuel during a range of time, could be a day or a month, etc. If the consumption was like the picture above would be easy.
The problem is that the data I have is li... |
H: Multivariate linear regression accounting for threshold / data cleaning
I am trying to make a linear regression model for the sale price of a house based on many variables (based on the data from this Kaggle challenge https://www.kaggle.com/c/house-prices-advanced-regression-techniques)
The distribution above is ... |
H: How to construct a Decision tree in R where the training data has a frequency associated with each class
Essentially, this is my data set
X Class Sex Age Survived Freq
1 1st Male Child No 0
2 2nd Male Child No 0
3 3rd Male Child No 35
4 Crew Male Child No 0
5 ... |
H: sklearn random forest and fitting with continuous features
Does anyone know how the python sklearn random forest implementation handles continuous variables in the fitting process? I'm curious to know if it does any sort of binning (and if so, how it does the binning), or if a continuous variable is just treated as... |
H: Deploying the prediction model under missing values for test data
I have successfully built a logistic regression prediction model based on data set that is complete and clean, i.e., there is no missing values and the data is consistent.
Now, for deploying the model and testing it for online use, there is missing v... |
H: Convert a pandas column of int to timestamp datatype
I have a dataframe that among other things, contains a column of the number of milliseconds passed since 1970-1-1. I need to convert this column of ints to timestamp data, so I can then ultimately convert it to a column of datetime data by adding the timestamp co... |
H: How to combine two CART decision trees learned in same type of data?
We have distributed data centers and we build decision trees in each data center. Our problem is to combine our CART decision trees into one CART decision tree. The data in each data center related to the same event (data from light sensor for ins... |
H: Use regression instead of classification for hard labeled ranking datasets
Let's imagine I have a dataset of movie reviews with annotated sentiment:
-1 means negative
0 means neutral
+1 means positive
I see a lot of people trying to do classification to try to answer those types of problems, but shouldn't regress... |
H: Neural network with flexible number of inputs?
Is it possible to create a neural network which provides a consistent output given that the input can be in different length vectors?
I am currently in a situation where I have sampled a lot of audio files, which are of different length, and have to train a neural netw... |
H: Why after adding categorical data the Linear Regression fails?
Based on a training set we applied a simple Linear Regression on some attributes that all were numeric.
Now we have more attributes in terms of categories and of course we applied one-hot-encoding to transform the categories to binary attributes
Take fo... |
H: Does the Bishop book imply that a neuron feeds to itself in chapter 5.3?
I just read Bishop's book Pattern Recognition and Machine Learning. I read the chapter 5.3 about backpropagation, and it said that, in a general feed-forward network, each unit computes a weighted sum of its inputs of the form $$a_j=\sum\limit... |
H: What is the difference of R-squared and adjusted R-squared?
I have in mind that R-squared is the explained variance of the response by the predictors. But i'd like to know how the adjusted value is computed ? and if the concept has any change from the original.
AI: A google search for r-squared adjusted yielded sev... |
H: Is there a network analysis tool built into Orange?
I am interested in a canned or built-in network analysis tool. Wondering if this is possible with Orange.
AI: This Networks add-on for Orange data mining suite should help you. If you are open to using other solutions, I would recommend networkx Python library. |
H: In Tensorflow, What kind of neural network should I use?
I am doing Tensorflow tutorial, getting what TF is. But I am confused about what neural network should I use in my work. I am looking at Single Layer Neural Network, CNN, RNN, and LSTM RNN.
-----------------------What I'm going to do is...--------------------... |
H: software for workflow integrating network analysis, predictive analytics, and performance metrics
I am hoping that there is some existing software for what I want to accomplish, as I'm not a big fan of reinventing the wheel.
In general, I would like a software package that can serve as a workflow that integrates ne... |
H: Feature selection and classification accuracy relation
One of the methodology to select a subset of your available features for your classifier is to rank them according to a criterion (such as information gain) and then calculate the accuracy using your classifier and a subset of the ranked features.
For example, ... |
H: Cost of greater than 1, is there an error?
I'm computing cost in the following way:
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(y, y_)
cost = tf.reduce_mean(cross_entropy);
For the first cost, I am getting 0.693147, which is to be expected on a binary classification when parameters/weights are initia... |
H: How to find splits in data so that each split has equal weighting according to function f
I have a weight function f that outputs a numeric weighting for a sample s. I also have an ordered set of samples S where the weight of each sample s in set S varies greatly.
How can I create n splitting points so that each sp... |
H: Python TypeError: __init__() got an unexpected keyword argument 'decision_function_shape'
I tried creating a SVM Classifier, as:
# Create a SVM Classifier
model = SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,
decision_function_shape=None, degree=3, gamma='auto', kernel='linear',
m... |
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