value prediction with tensorflow and python

I have a data set which contains a list of stock prices. I need to use the tensorflow and python to predict the close price. Q1: I have the following code which takes the first 2000 records as training and 2001 to 20000 records as test but I don't kn

ValueError: Can not convert string to float:

I am following a this tutorial to write a Naive Bayes Classifier: I keep getting this error: dataset[i] = [float(x) for x in dataset[i]] ValueError: could not convert string to

Export neural network weights using tensorflow

I wrote neural-network using tensorflow tools. everything working and now I want to export the final weights of my neural network to make a single prediction method. How can I do this?You will need to save your model at the end of training by using t

Can someone explain me StandardScaler?

I am unable to understand this Can anyone explain this to me in simple terms?The idea behind StandardScaler is that it wil

How to learn to learn (Tree) on several attributes?

I am using python and scikit-learn's tree classifier in a little fictive machine learning problem. I have binary outcome variable (wc_measure) and I believe it is dependent on a few other variables (cash, crisis, and industry). I tried the following:

How can I form a neural network from many datasets?

I have many sets of related data that I want to use to train a neural network. The data is from racing pigeons that fly a set distance. The inputs could be weight, age, size, wing span, sex, distance, time etc. sampled lets say every minute. I am try

Datasets cached by different versions of Vowpal Wabbit

Due to certain reasons, I'm using 2 different VW releases: the latest development version (8.1.1) for my experiments, and the "latest stable" 7.10 release for production. So, the question is: what happens if I simply specify -c flag for the prod

Is there a classifier able to make decisions very quickly?

Most classification algorithms are developed to improve the training speed. However, is there any classifier or algorithm focusing on the decision making speed(low computation complexity and simple realizable structure)? I can get enough training dat

Image recovery based on content?

Well I googled about Content Based Image Retrieval(CBIR) and actually the wiki definition is quite clear but there is not much material nor books related to subject. Can anyone explain what are the components that comprise Content Based Image Retriev

SVM ranking only works on tiny datasets

I am using svm-rank. When running svm_rank_learn on a tiny dataset: Training set properties: 3 features, 12 rankings, 596 examples The run finishes in a few seconds and I get a valid model. But when I use a bit larger dataset: Training set properties

Use of the decision tree in recommendation systems

I have a decision tree that is trained on the columns (Age, Sex, Time, Day, Views,Clicks) which gets classified into two classes - Yes or No - which represents buying decision for an item X. Using these values, I'm trying to predict the probability o

Have a learn batch program

I am making a chat bot for my sister in batch but it is consuming so much time I figured I would let it have her tell it what to say when it does not know. However I can not get it working and I figured someone on here might know. Here is what I have

How can KMeans be used to say that a dataset has noise?

I have come across an extract from an old paper which casually mentions, If required, we could use KMeans as a method of asserting that this dataset is noisy, thus proving that our classifier working as well as can be reasonably expected. I can find

Cross validation in sklearn python

I am using python sklearn library for doing classification of data. Following is the code I have implemented. I just want to ask, is this correct way of classifying? I mean can following code potentially remove all the biases? And, is it 10-k fold cr

Categorized dataset for emotion recognition

I work with some research educational task and need dataset with classified facial emotions to train classifier. For example, gender classification is simple: I can create csv file, and mark any file with image as 0 or 1, according to gender. Somethi

Can TF / IDF take courses into account

Using a classsication algorythm (for example naive bayes or SVM), and StringToWordVector, would it be possible to use TF/IDF and to count terms frequency in the whole current class instead of just looking in a single document? Let me explain, I would

Fastest approximate counting algorithm

Whats the fastest way to get an approximate count of number of rows of an input file or std out data stream. FYI, this is a probabilistic algorithm, I can't find many examples online. The data could just be one or 2 columns coming from an awk script

No mahout java - Canopy clustering implementation

I have my own java based implementation of clustering (knn). However I am facing scalability issues. I do not plan to use Mahout because my requirements are very simple and mahout requires lot of work. I am looking for java based Canopy clustering im

Conditional random fields

Is there a training and optimization algorithm for 2-D (two dimensional) conditional random fields (CRF) suited for classification of imagery? Has anyone used CRF package in R ( for image classif

Size of the neural network for the animation system

I decided to go with a Neural Network in order to create behaviors for an animation engine that I have. The neural network takes in 3 vector3s and 1 Euler angle for every body part that I have. The first vector3 is the position, the second is its vel