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H: How to self-learn data science?
I am a self-taught web developer and am interested in teaching myself data science, but I'm unsure of how to begin. In particular, I'm wondering:
What fields are there within data science? (e.g., Artificial Intelligence, machine learning, data analysis, etc.)
Are there online classe... |
H: Code Vectorization of gsub in R
How can I vectorize this code in R?
data <- data.frame(A = rep(5, 5), B = rep(0, 5))
data$abstract <- c("no abstract available", "A", "A", "B", "no abstract available")
for (row in (1:nrow(data))){
data [row,"abstract"] <- gsub("no abstract available"," ",data[row,"abstract"])
}
A... |
H: When to use One Hot Encoding vs LabelEncoder vs DictVectorizor?
I have been building models with categorical data for a while now and when in this situation I basically default to using scikit-learn's LabelEncoder function to transform this data prior to building a model.
I understand the difference between OHE, La... |
H: Pandas: how can I create multi-level columns
I have a pandas DataFrame which has the following columns:
n_0
n_1
p_0
p_1
e_0
e_1
I want to transform it to have columns and sub-columns:
0
n
p
e
1
n
p
e
I've searched in the documentation, and I'm completely lost on how to implement this. Does... |
H: R: lattice equivalent of density2d in ggplot?
What would be the equivalent of geom_density2d in lattice? In essence I'm trying to create this graph with lattice:
I don't think contourplot or levelplot is what i want and when trying it, it gives me a blank plot?
AI: Use a custom panel function in which the density ... |
H: nlp - opinion mining vs sentiment analysis
I have been told that nlp possibly holds the key for allowing researchers to infer the affective state of a person when writing. For instance, by using nlp analysis on online note taking you could infer whether a student is stressed. I work in educational cognitive science... |
H: XGBoost Linear Regression output incorrect
I am a newbie to XGBoost so pardon my ignorance. Here is the python code :
import pandas as pd
import xgboost as xgb
df = pd.DataFrame({'x':[1,2,3], 'y':[10,20,30]})
X_train = df.drop('y',axis=1)
Y_train = df['y']
T_train_xgb = xgb.DMatrix(X_train, Y_train)
params = {"o... |
H: xgboost: give more importance to recent samples
Is there a way to add more importance to points which are more recent when analyzing data with xgboost?
AI: You could try building multiple xgboost models, with some of them being limited to more recent data, then weighting those results together. Another idea would ... |
H: Binary Neural Network Classification or Multiclass Neural Network Classification?
I am confused about the difference between a binary and multiclass neural network classification. If I am writing an algorithm that has 2 output classes (Obama or Romney), but not yes or no (so not like Obama or not Obama), then is it... |
H: Properties for building a Multilayer Perceptron Neural Network using Keras?
I am trying to build and train a multilayer perceptron neural network that correctly predicts what president won in what county for the first time. I have the following information for training data.
Total population Median age % BachelorsD... |
H: Where does the name 'LSTM' come from?
Long short-term memory is a recurrent neural network architecture introduced in the paper Long short-term memory.
Can you please tell me where the name comes from?
("Memory", as the network can store information because of the recurrence - but where does the "Long short-term" c... |
H: Are there other large margin classifiers than SVMs?
When reading about SVMs (e.g. on the German Wikipedia) there is a sentence like "an svm is a large-margin classifier).
Are there other large margin classifiers than SVMs?
AI: Yes, one famous example are boosting techniques like Adaboost. It uses small classifiers ... |
H: Recognition human in images through HOG descriptor and SVM classifier performs poorly
I'm using a HOG descriptor, coupled with a SVM classifier, to recognise humans in pictures. I'm using the Python wrappers for OpenCV.
I've used the excellent tutorial at pymagesearch, which explains what the algorithm does and fur... |
H: Where exactly does $\geq 1$ come from in SVMs optimization problem constraint?
I've understood that SVMs are binary, linear classifiers (without the kernel trick). They have training data $(x_i, y_i)$ where $x_i$ is a vector and $y_i \in \{-1, 1\}$ is the class. As they are binary, linear classifiers the task is to... |
H: How to select regression algorithm for noisy (scattered) data?
I am going to do regression analysis with multiple variables. In my data I have n = 23 features and m = 13000 training examples. Here is the plot of my training data (area of houses against price):
There are 13000 training examples on the plot. As you ... |
H: How is it possible to process an image with a few neurons?
An 1024*1024 pixel image has around one million pixels. If I would like to connect each pixel to an R,G,B input neuron, then more than 3 million neurons are needed.
It would be really hard, to train a neural network, which has millions of inputs. How is it ... |
H: Stacked features not helping
I am wondering why my stacked features do not help me to improve against my loss metric. Here's what I'm doing: I am adding new features which are simple the predictions originated from train, predict of other models to the original train/test features. Every time I have tried this me... |
H: Research in random forest algorithms able to switch data sets
I'm curious as to whether research been done into random forests that combine unsupervised with supervised learning in a way allowing a single algorithm to find patterns in, and work with, multiple different data sets. I have googled every possible way t... |
H: Using R and Python together
I'm new in this field and I started working with data by using R. Because of that, I find R much easier to approach a data project. However, apparently an employer wants you to know an object-oriented programing language (a language like Python).
So it would be smart to think I can use ... |
H: Neural Networks for Predictive typing
I don't have a background in neural networks. But, various studies has been proved that neural networks (feed forward / Recurrent) outperformed n-gram language modeling for predicting words in a sequence. But, in an application to text messaging or any text-based conversation, ... |
H: supervised learning and labels
In this wiki page, I came across with the following phrase.
When data is not labeled, a supervised learning is not possible, and
an unsupervised learning is required
I cannot figure out why supervised learning is not possible?
Appreciate any help to resolve this ambiguity.
AI: The... |
H: Software Testing for Data Science in R
I often use Nose, Tox or Unittest when testing my python code, specially when it has to be integrated with other modules or other pieces of code. However, now that I've found myself using R more than python for ML modelling and development. I realized that I don't really test ... |
H: Tokenizing words of length 1, what would happen if I do topic modeling?
Suppose my dataset contains some very small documents (about 20 words each). And each of them may have words in at least two languages (combination of malay and english, for instance). Also there are some numbers inside each of them.
Just out o... |
H: Building a machine learning model to predict crop yields based on environmental data
I have a dataset containing data on temperature, precipitation and soybean yields for a farm for 10 years (2005 - 2014). I would like to predict yields for 2015 based on this data.
Please note that the dataset has DAILY values for ... |
H: Machine learning algorithm to classify blog posts
So I have a large collection of blog posts containing title, content, category, tags and geo-location fields and I'm looking to achieve three things:
Assign a category (or multiple categories) to all the posts and any new ones. I have a strict vocabulary of categor... |
H: Open cv and computer vision
I'm new to computer vision, and I'm looking for a good place to start from, what's better between open cv in python or open cv in c++
AI: Depends on your programming skills. Here is the summary:
OpenCV is a great tool originally developed in C++ and after a while a Python interface was a... |
H: Spike Slab in r, bad output
I've successfully used Spike Slab in the past, but with this data it seems like something is going wrong. My code is:
>require(spikeslab)
>set.seed(2)
>model1_ss<-with(data_use,spikeslab(gdeaths_per_100_thousand~gdealers_per_100_thousand+Physically.Unhealthy.Days+Mentally.Unhealthy.Days,... |
H: Assigning values to missing target vector values in scikit-learn
I have a dataset containing data on temperature, precipitation, and soybean yields for a farm for 10 years (2005 - 2014). I would like to predict yields for 2015 based on this data.
Please note that the dataset has DAILY values for temperature and pre... |
H: How can I use data on customer interactions to drive communication strategy?
I have data on my customers (age, location, gender) and number of interactions with customer by channel (#calls, #sms, #letters) and data on whether they have bought a product (yes/no).
I would like to predict what combination of interacti... |
H: How to prepare colored images for neural networks?
I have seen many examples online regarding the MNIST dataset, but it's all in black and white. In that case, a 2D array can be constructed where the values at each array element represent the intensity of the corresponding pixel. However, what if I want to do color... |
H: Mine webshop history for clusters
I've no experience in data science so this will be one of those questions...
I have data from >100k purchases made via a webshop regarding a catalogue of around >100 items. The history of purchases flattened out looks like
Item1 Item2 ... ItemN Sex State
5 0 0 M ... |
H: Simple example of genetic alg minimization
I have been looking for a while for examples of how I could find the points at which a function achieves its minimum using a genetic algorithm approach in Python. I looked at DEAP documentation, but the examples there were pretty hard for me to follow. For example:
def f... |
H: Writing custom data analysis program
I have a number of large datasets (10GBs) each with data fetched from a NoSQL database that I have remotely downloaded on my desktop. I would like to write a Python program to run some custom data analysis (plots - preferably interactive) and export custom reports in html or pdf... |
H: Pandas: access fields within field in a DataFrame
Suppose I have such a JSON file:
[
{
"id": "0",
"name": "name0",
"first_sent": "date0",
"analytics": [
{
"a": 1,
...
},
{
"a": 2,
...
}
]
}
]
and I want to ... |
H: Python: validating the existence of NLTK data with database search
I need to pull the names of companies out of resumes. Thousands of them. I was thinking of using NLTK to create a list of possible companies, and then cross-referencing the list of strings with something like SEC.gov.
I've already been able to succe... |
H: Rules by which RStudio sets Headings
RStudio automatically recognizes headers in an R script that are set via comments:
I would like to exploit that feature, but I don't quite understand what the rules are for RStudio to recognize them as headers. Can someone explain?
AI: Check out Code Folding and Sections:
Co... |
H: Mathematics major for data science
So I'm a recent transfer 2nd year student from Computer Science major to Mathematics major. Though I do have a bit of an issue here. I can choose between the applied mathematics, pure mathematics and statistics concentrations.
Along with this major, I'm doing a minor in Data Scien... |
H: How data representation affects neural networks?
Suppose A's possible values are ON or OFF.
Suppose I represent it as: if A ON then feature f=1 else f=0
Or, suppose I represent it with 2 features, where:
-if A is ON then f1=1 and f2=0
-if A is OFF then f1=0 and f2=1
How this kind of representation affects neural ... |
H: Please list some well tested api's for arima model
I am looking for a good python api for timeseries models such as ARIMA. Please list some well tested apis and few more advance models possible for financial time-series analysis.
AI: Statsmodels:
Statsmodels is your best bet for a python library that includes ARIMA... |
H: Approximating density of test set in train
I am looking for a method to approximate how similar a test set (i.e., test set features) to a train set. For example, something like, for each row in test: is there a similar enough data point in train? I've been thinking about using a mixture model approach, but I haven... |
H: is neural networks an online algorithm by nature?
I have been doing machine learning for a while, but bits and pieces come together even after some time of practicing.
In neural networks, you adjust the weights by doing one pass (forward pass), and then computing the partial derivatives for the weights (backward pa... |
H: what is the difference between "fully developed decision trees" and "shallow decision trees"?
As reading Ensemble methods on scikit-learn docs, it says that
bagging methods work best with strong and complex models (e.g., fully
developed decision trees), in contrast with boosting methods which
usually work best... |
H: Question about train example code for TensorFlow
I am trying to learn TensorFlow, and I could understand how it uses the batch in this example:
cross_entropy = -tf.reduce_sum(y_*tf.log(y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
correct_prediction = tf.equal(tf.argmax(y_conv,1), tf.ar... |
H: Predicted features combined with original ones
I am currious how good such a procedure could be :
I get some predictions of some 10 learners trained on train set and predicted on train set also .
Then I am column binding those predictions to the original train.
Could this be a valid procedure on imp... |
H: What kinds of learning problems are suitable for Support Vector Machines?
What are the hallmarks or properties that indicate that a certain learning problem can be tackled using support vector machines?
In other words, what is it that, when you see a learning problem, makes you go "oh I should definitely use SVMs f... |
H: Overfitting/Underfitting with Data set size
In the below graph,
x-axis => Data set Size
y-axis => Cross validation Score
Red line is for Training Data
Green line is for Testing Data
In a tutorial that I'm referring to, the author says that the point where the red line and the green line overlap means,
Colle... |
H: Feauture selection for clustering regarding zero-correlated feature
I want to cluster a 5 feature data-set. Firstly to explore the data I did a correlation matrix to see if some features where highly correlated so I could reduce them. Then I saw a feature that have close to zero correlation against all the other fe... |
H: What is a Recurrent Heavy Subgraph?
I recently came across this term recurrent heavy subgraph in a talk. I don't seem to understand what it means and Google doesn't seem to show any good results. Can someone explain what this means in detail.
AI: The term may best be expressed as a Recurrent, Heavy Subgraph. That i... |
H: Best regression model to use for sales prediction
I have the following variables along with sales data going back a few years:
date # simple date, can be split in year, month etc
shipping_time (0-6 weeks) # 0 weeks means in stock, more weeks means the product is out of stock but a shipment is on the way to the w... |
H: Using machine learning specifically for feature analysis, not predictions
I'm new to machine learning and have spent the last couple months having a blast using Sci-Kit Learn to try to understand the basics of building feature sets and predictive models.
Now I'm trying to use ML on a data set not to predict future ... |
H: How to define person's gender from the fullname?
Given person's name, e.g. 'Adjutor Ferguson'.
How to define is it a male or female?
One solution came to my mind:
I have found Person NLP training dataset here mbejda.github.io.
And via a machine learning software like Apache Mahout, train it and provide ... |
H: Face Recognition using Eigenfaces and SVM
I am new to machine learning. I want to develop a face recognition system using scikit-learn. This is the example given in the tutorials of scikit-learn.
I am not getting how the input is being provided to the program. How should I load a particular image and make my progra... |
H: Is there any domain where Bayesian Networks outperform neural networks?
Neural networks get top results in Computer Vision tasks (see MNIST, ILSVRC, Kaggle Galaxy Challenge). They seem to outperform every other approach in Computer Vision. But there are also other tasks:
Kaggle Molecular Activity Challenge
Regres... |
H: Ensemble Model vs Normal model
If I get 95+ % accuracy in normal models, should I still consider Ensemble models? Why should I choose Ensemble models over normal models?
AI: Firstly, welcome to the site!
When do we use Ensemble model?
when there are 2 models which perform moderately then we combine their results t... |
H: Warning message in randomForest
I want to applicate the randomForest to my data for predicting target variable, but I have got a warnings message saying:
Warning message:
In randomForest.default(m, y, ...) :
The response has five or fewer unique values. Are you sure you want to do regression?
I didn't know what... |
H: Text classification problem using Python or R
I am a novice in machine learning and new to NLP. I am looking for ideas on how to solve the below two problems.
I have a dataset with two columns, "Titles" and "Description". Titles column has names of clinical lab tests and description column has description about res... |
H: Some questions about feature hashing in the context of document classification
I'm trying to understand feature hashing, specifically in the context of document classification.
I'm under the impression that it is useful because:
it allows us to easily deal with 'new' words/features/predictors that we haven't seen... |
H: Input normalization for ReLu?
Let's assume a vanilla MLP for classification with a given activation function for hidden layers.
I know it is a known best practice to normalize the input of the network between 0 and 1 if sigmoid is the activation function and -0.5 and 0.5 if tanh is the activation function.
What abo... |
H: What is the BLEU score used in Google Brain's "Attention Is All You Need" paper?
Google Brain's Attention Is All You Need paper on sequence-to-sequence translation reports:
Our model achieves 28.4 BLEU on the WMT 2014 Englishto-German
translation task, improving over the existing best results, including
ensemb... |
H: Features selection/combination for random forest
I am working on using random forest to predict 1 or 0. I have about 20 variables available for modeling. I realized that if I put different variables will have different accuracy/sensitivity/specificity. I am wondering if there is a test or method can tell me which v... |
H: XGBoost Classification Probabilities higher than RF or SVM?
I am using Random Forests, XGBoost and SVMs to classify whether the home team wins or the away team wins their bowl game (in college football). I trained the models on all the games during the season.
I've come across something that is a bit weird and can'... |
H: What are similarity and distance metrics in classification?
I have an assignment to train a model to classify text data, the brief for the assignment mentions that any for any learning model used I have to provide a reasoning for the similarity or distance metric used. What does this refer to?
My initial thought wa... |
H: Does keras categorical_cross_entropy loss take incorrect classification into account
I was looking at keras source here which calculates cross entropy loss using:
output /= tf.reduce_sum(output,
reduction_indices=len(output.get_shape()) - 1,
keep_dims=True)
# manual c... |
H: ANN on Pattern Recognition
I have been trying to apply a simple neural network using keras to predict a sequence of numbers and the rule is if the input integer is odd it should be 4 and if its even it should be 2. Yet the neural network gets stuck at a 60% accuracy rate. Anyone know a solution to this?
from keras.... |
H: Small amount of training data set for naive Bayes classifier for binary classification
I'm implementing prediction system for young cricketers in ODI format using Naive Bayes classifier. The output of the system is to predict whether the young player is rising star or not. I have collected data from statsguru API o... |
H: Multiclass classification with Neural Networks
Let’s suppose I wanted to classify some input as one of three categories using a simple neural network.
The output of my network are three columns (one for each possible category I assume) with values between 0 and 1. Moreover, the single rows add up to precisely one w... |
H: Difference between interpolate() and fillna() in pandas
Since interpolate and fillna method does the same work of filling na values. What is the basic difference between the two. What is the significance of having these two different methods?? Can anyone explain me in layman terms. I already visited through the off... |
H: Is there a way to set a different activation function for each hidden unit in one layer in keras?
I'm trying to set a different activation function for each hidden unit in a layer. Is this possible in Keras with 'Concatenate'?
AI: If I get the point, you can use a similar code like the following:
from keras.layers ... |
H: CUDA_ERROR_OUT_OF_MEMORY
I have a large network that is somewhat similar to Wavenet. Although (it seems) that my GPU has enough memory, I get an out of memory error on fitting (see logs below).
Any idea?
How can I troubleshoot these kind of CUDA driver issues?
2017-12-22 23:32:05.288986: I C:\tf_jenkins\home\works... |
H: Should the input data be normalized using keras pre-trained models
I want to use a pre-trained VGG16 in keras. My question is simple. Should I normalize the input image before predicting its label?
AI: According to Very Deep Convolutional Networks for Large-Scale Image Recognition, which is the paper that first pre... |
H: Backpropagation in other fields
Powerful techniques are sometimes rediscovered by various disciplines at different points in time, because the particular scientific fields do not overlap or interact.
A couple of ML researchers have pointed out, that the back-propagation (Rumelhart et al, 1986) algorithm (a solution... |
H: Feature agglomeration: Is it testing interactions?
I have been looking at feature agglomeration in Python's scikit-learn. According to the user guide, feature agglomeration "applies Hierarchical clustering to group together features that behave similarly". Does this mean it is testing for interactions between featu... |
H: Evaluating machine learning model with missing features
I am working on a credit risk binary classification problem. The classes are GoodPayers and BadPayers. The training set has variables/features that contains:
DemoGraphics Data such as - Age, Education, Loan Amount, Interest Rate
Behavioral Data such as - P... |
H: Error 'Expected 2D array, got 1D array instead:'
While performing a simple fitting operation on the Titanic dataset. The following is my code:
data = pd.read_csv(r'.\Desktop\DS\Titanic\train.csv')
sex_train = data['Sex'].map({'male':0,'female':1})
survived_train = data['Survived']
sex_survivor_tree = GaussianNB()
s... |
H: Is there an intuitive explanation why some neural networks have more than one fully connected layers?
I have searched online, but am still not satisfied with answers like this and this.
My intuition is that fully connected layers are completely linear. That means no matter how many FC layers are used, the expressiv... |
H: Set for building ROC curve and and choosing logistic regression cut-off
I'm building a logicsic regression classifier for binary classification. I have trained it and going to choose a cut-off value using ROC curve.
But what set to use for it: training or validation?
AI: Usually you need to generate the ROC curve a... |
H: Questions about CNN: weights and biases
I have a question regarding CNN.
I do understand how they work on the surface. Very simply put, they are D-NN for images.
I'll use this example as a reference for this question. In the example, they are not initializing weights and biases anywhere. They are using tf.layers.co... |
H: python sklearn decision tree classifier feature_importances_ with feature names when using continuous values
I'm using sklearn Decision Tree Classifier with some continuous features.
When I run export_graphviz I see the same features in more than one nodes and with different values. Example:
I would like to take t... |
H: When using numerical duplicates for categorical data, new columns should be added or values be converted?
If this is the dataframe, in pandas
+--------+--------+-------+
| Col1 | Col2 | Sex |
+--------+--------+-------+
| Value | Value | F |
| Value | Value | M |
| Value | Value | M |
| Valu... |
H: Negative Rewards and Activation Functions
I have a question regarding appropriate activation functions with environments that have both positive and negative rewards.
In reinforcement learning, our output, I believe, should be the expected reward for all possible actions. Since some options have a negative reward, ... |
H: Hadoop and input informations divided in splits
Hadoop divides the input to a MapReduce job into fixed-size pieces
called input splits, or just splits. Hadoop creates one map task for
each split, which runs the user-defined map function for each record
in the split. Having many splits means the time taken to... |
H: What is the tag mapping for entity recognition in nltk?
When doing entity recognition using NLTK, one gets as a result a Tree with a bunch of words mapped to tags (eg. Mark -> NNP, first -> JJ, ...). It's not at all clear what all the tags stand for at first glance and I was unable to find any documentation about t... |
H: Unable to print in Jupyter Notebook using Pandas
I am doing basic data analysis on an csv file in jupyter notebook
def answer_two():
return (df['Gold']-df['Gold.1']).argmax()
answer_two
The above code snippet is to subtract two columns of the dataframe.I am expecting an answer in the form of a country name but... |
H: Non trainable problems
Before facing this question, I always thought non-learnable problems are those which the provided data for the problem has high amount of outliers, those which don't have sufficient features or those for which the Bayes error is large because of having same features with different labels. As ... |
H: Testing fit of probability distribution
If I have fitted training data to a probability distribution, e.g. a poisson distribution, how can I test this fit on some test data?
To fit the poisson distribution I am using R's fitdistrplus package that using MLE for determining the optimal coefficients of a given distrib... |
H: Which classification algorithms can handle 24000 features
Which classification algorithms can handle 24000 features? What are their pros and cons?
AI: Deep Learning Algorithms and Graphical model algorithms can handle that scale of features.
For example a typical parsing algorithm using CRF++ computes millions of f... |
H: Is it legal to scrape YouTube videos for training data?
Is it legal, at least as long as I am not "selling" the video under my name, to scrape YouTube videos to train a neural network?
If it is not, is there a procedure to get permission for the above? I am in academia and require a massive amount of video data tha... |
H: how does minibatch for LSTM look like?
Minibatch is a collection of examples that are fed into the network, (example after example), and back-prop is done after every single example. We then take average of these gradients and update our weights. This completes processing 1 minibatch.
I read these posts
[1]
[2],... |
H: state-action-reward-new state: confusion of terms
My question may sound like a duplicate of, for example, How is that possible that a reward function depends both on the next state and an action from current state?
but I still feel confused.
In neural network approximation of the Q function, I follow the experience... |
H: Merging two different models in Keras
I am trying to merge two Keras models into a single model and I am unable to accomplish this.
For example in the attached Figure, I would like to fetch the middle layer $A2$ of dimension 8, and use this as input to the layer $B1$ (of dimension 8 again) in Model $B$ and then com... |
H: Initialize perceptron weights with zero
I'm new to datascience so please just don't blast me.
In a text book i found:
Now, the reason we don't initialize the weights to zero is that the
learning rate (eta) only has an effect on the classification outcome
if the weights are initialized to non-zero values. If al... |
H: Classify text labels in to a similar category
I'm trying to classify same kind of text labels in to one category. For example, if I have labels like qty, quantity, qty_no all of them should direct to Quantity. Since I'm new to data science, what's the best way to start this kind of thing?
AI: One way to do it could... |
H: Neural network without matrices
Have you ever seen a neural network without matrices?
I'm asking, because I'm currently building one for educational purposes.
AI: Matrix multiplication is just a simplified notation for a particular set of addition and multiplication operations. You can absolutely represent a neural... |
H: Cluster titles or ingredients of food into n-categories
I have a dataset which has information about food recipes (in german), that looks like this:
Here is a link to a small .csv file (first 1000 rows of my data)
https://drive.google.com/file/d/1C7thFlOnDn-oTc6AaDWA3CXXcX8m9NRu
The idea is to cluster the recipe n... |
H: Facing a difficult regular expression issue in cleaning text data
I am trying to substitute a sequence of words with some symbols from a long string appearing in multiple documents. As an example, suppose I want to remove:
Decision and analysis and comments
from a long string. Let the string be:
s = Management's d... |
H: How does decision tree for regression makes a prediction?
For classification, it is obvious how a decision tree is used to make a prediction.You just have to find the final leaf. However for regression problems, how can you find the prediction considering the continous aspect of the variable to predict?
AI: Depends... |
H: Clustering Data to learned cluster
I am new to data science, I have clustered some data using Scipy agglomerative clustering. how can I fit new data into the learned clusters?
dm = pdist ( dataset ,lambda u,v: mlpy.dtw_std ( pd.Series(u).dropna().values.tolist(),pd.Series(v).dropna().values.tolist(),dist_only=True ... |
H: Parzen and k nearest neighbor
I have this formula for the density estimation.
$$p_n(x) = \frac{k_n / n}{V_n}$$
I have been told that with a Parzen window approach you can specify $V_n$ as a function of $n$. So if $V$ decreased when $n$ increased it is clear that it is a fixed volume.
I have also been told that wit... |
H: calculate distance between each data point of a cluster to their respective cluster centroids
I have a dataset of some keywords in some text files. Using the append feature I have access each text file and I append all of the keywords to token_dict like this
token_dict="wrist. overlapping. direction. receptacles. ... |
H: Why is training take so long on my GPU?
Details:
GPU: GTX 1080
Training: ~1.1 Million images belonging to 10 classes
Validation: ~150 Thousand images belonging to 10 classes
Time per Epoch: ~10 hours
I've setup CUDA, cuDNN and Tensorflow( Tensorflow GPU as well).
I don't think my model is that complicated that is t... |
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