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H: What is the best approach for classifying non-English text
What would be the best approach for classifying non-English (Sinhala / Tamil) text? Currently I use Fasttext. Are there any better options?
I want to classify user questions into chatbot intents. Therefore, there may be many target classes.
AI: As far as I... |
H: Why SVM gridsearch takes longer time?
I have a dataset of 5K records and 60 features focussed on binary classification. Please find my code below for SVM paramter tuning. It's running for a longer time than Xgb.LR and Rf. The other algorithms mentioned returned results within minutes (10-15 mins) whereas SVM is run... |
H: How to yield better AUC score?
I have a dataset with 5K records and 60 features focused on binary classification. Class proportion is 33:67
Currently I am trying to increase the performance of my model which is stuck at F1-score of 89% (majority) and 75% (minority) class and AUC of 80%.
I tried Gridsearchcv and fe... |
H: What's wrong with RF/SVM with word embedding (GloVe)?
I searched many times in google for examples on word embedding (specifically GloVe) with Random forest and I couldn't find any single example. For GloVe, it was all either LSTM or CNN. Maybe there's something I don't understand, but why only these 2 algorithms a... |
H: How can I compare the contribution of two predictors in two different sorts for machine learning algorithms?
I'm new to machine learning and try to clarify my problem in research. I just wonder if I can compare the importance of two different variables in two different sorts. For example, A and B are two variables ... |
H: What does many low important feature indicate?
I have a dataset where I am focusing on binary classification problem. In total,I have around 60 features in my dataset
When I used Xgboost Feature Importance, I was able to see that the top 5 features account for 42% whereas rest of the of the 50 features account for ... |
H: How to best use geographical information as a factor?
I am trying to predict crime rates and I have naively used lat and long as two separate factors (which seem to work well!). Are there any best practices for location as a factor?
AI: If you are predicting crime rates in a certain region, we may use clustering to... |
H: Efficient recurrent network for sequences of varying length
Suppose I have a bunch of sequences of varying lenghts. The absolute majority of them are short, just a few dozens items long. However, very few of them are significantly longer - more than a hundred items long. The question is, how to organize them effici... |
H: Which kNN model to chose?
I am trying to tune the "n_neighbors" for a kNN model andI have the following problem :
Based on the mean cross validation score the optimal kNN model should be the one with 10 neighbors.
On the other hand, when I plot the "scores vs neighbors" graphs I see that there are models whose sc... |
H: Recommended data cleaning techniques for multivariate time series prediction?
I have to predict the next step(s) in a multivariate time series with about 30 features and 50.000 samples. I am thinking of using LSTM. Which techniques are usually recommended for cleaning the data when using LSTM?
Does it make sense to... |
H: K-Fold Cross Validation for NNs
When using K-Fold CV, is it still useful to have a Train/Validation/Test split?
Or simply just a Train/Test? I.e. split up data into k bins, and leave one out for testing, train on the rest, and take average of the scores.
AI: It depends. If you're evaluating your model's performanc... |
H: How to interpret coefficients from logistic regression?
I ran a logistic regression (statsmodel) on my data with 60 features using the below code
import statsmodels.api as sm
logit_model=sm.Logit(y_train,X_train_std)
result=logit_model.fit()
print(result.summary())
I was able to see that few variables had negative... |
H: How to pass linear regression weights to Xgboost regressor?
I'm trying to build an xgboost regressor or a catboost regressor for a task. I have a working linear regression model. I also trained an xgboost regressor model for the task but it was worse than the linear regression model. I am wondering if there is a wa... |
H: Pandas dataframe with multiple observations per model
I currently have a pandas dataframe with the following format
Model Metric Value
--------------------------------------------------------------
0 Ours Accuracy [0.79, 0.79, 0.82]
1 Theirs Accuracy [0.68, 0.56, 0.64]
2... |
H: How to get significance level for ranked features?
I am aware of below approaches of feature selection
a) Feature Importance methods which are available in tree based models like Random Forest and Xgboost,GradientBoost etc.
b) statsmodel.logistic regression which in it's summary output provide us the results which ... |
H: unique predictions for "multi-label multi-output" classification task
Let’s assume that four participants (A, B, C and D) take on five sport-challenges (e.g. swimming, running, ...). Our goal is to predict the placement of each participant for each challenge. Moreover, let’s assume we have appropriate predictors. W... |
H: Proper masking in the transformer model
Concerning the transformer model, a mask is used to mask out attention scores (replace with 1e-9) prior to the matrix multiplication with the value tensor. Regarding the masking, I have 3 short questions and would appreciate if you could clarify those:
Are the attention scor... |
H: What's a good F1-score in (not) extremely imbalanced dataset?
I have a dataset with around 4.7K focused on binary classification. Class proportion is 33:67. meaning Label 1 is 1558 (33%) and Label 0 is 3154 (67%) of my dataset.
Is my dataset imbalanced? some people say it is not bad
My objective is to increase the ... |
H: Can 2 different OOV words get the same vector in FastText?
Since FastText sums up the vectors(order is not considered) of an OOV word's subwords, is it possible for two different OOV words to get the same vector ? If so, then can you give an example?
AI: TL;DR
Theoretically it is possible, but it is unlikely.
1) Un... |
H: which is better : F1-score of 'N' in imbalanced data or 'N+3' in balanced data?
I have a dataset with 4712 records. Label 1 is 1558(33%) and Label 0 is 3154 (67%)
a) Currently when I run the model and analysis as is (without sampling techniques), I get an F1-score of 71-77. I chose F1-score and AUC score as the me... |
H: How to perform convolution with kernel bigger than image?
In this question I've seen an example of convolution by the kernel with the shape bigger than initial image's one:
import numpy as np
from scipy import signal
x = np.array([(0.51, 0.9, 0.88, 0.84, 0.05),
(0.4, 0.62, 0.22, 0.59, 0.1),
... |
H: CrossMapLRN2d in pytorch
I had to convert a code written in pytorch to keras (with tensorflow backend). But there was this layer called CrossMapLRN2d which had no direct counterpart in Keras. So wanted to know what does this layer do and how to implement it in keras.
The exact line of code was
nn.CrossMapLRN2d(siz... |
H: Training a Siamese Neural Network for object similarity assessment
I am training a Siamese neural network with pairs of similar and dissimilar objects. The features of the objects are binary data on whether they contain some properties or not (2048 features per object).
I then split my dataset into training, valid... |
H: Get the Polynomial Equation with Two Variables in Python
TL;DR
predict "price", given "length" and "wandRate"
I have some time-series data where the dependent variable is a polynomial result of 2 independent data points.
Here is a snippet:
This is past pricing data of Processed Rice Grains of a certain kind of r... |
H: One scaler for all features or one scaler per feature?
I have a time series with more than 30 features. For preprocessing with scikit learn do you usually use one scaler per feature or one scaler for all features that should be standardized/normalized?
AI: Sklearn scaler works on feature/column (and thats why you w... |
H: Technique to determine variation in metric due to varying parameters
So basically I have a large set of features corresponding to a metric - like many ML problems.
What I want to know is: can we correlate the variance of metric with the variation in each feature.
ex:
I have features x, y, z that produce an output s... |
H: How to choose input variables for ML
Let's say I have a huge database with 100K records and 60 columns. Let's say one of the column is "min_p". What I do is apply some logic/rule to determine the output label for this record. Basically I look at previous two records and next two records of this min_p. If the condit... |
H: Does Sklean's SGDClassifier automatically standardize the training data when regularization is turned on?
Generally speaking--it is best to apply standarizaton (z-scoring the training data) prior to regularization. Does sklearn.linear_model.SGDClassifier automatically standardize the training data or not when the '... |
H: Decision Tree Classifier to classify values based on values of other columns
I have data with multiple labels, for example
My X set is fromt second to third column, and I want to classify either first column or the last column, so I made my Y the last column.
The goal is so that if I would classify Vios it would r... |
H: KMeans clustering for Image Data
I am trying to cluster the sample of Imagenet Dataset using K-Means clustering.
In this approach, I have used the below 2 approaches to get the optimal number of clusters.
Elbow method From the Graph it seems like the best number of clusters is from 6 to 10.
Silhouette score
... |
H: Format of data in SQL for machine learning
I am a beginner at Machine Learning and am starting out on a ML project. I have a large chunk of the source material and have started extracting the data from it to be stored in SQL (initial test with SQLite, but that is going to be insufficient for production).
The questi... |
H: Is there any good practice to cluster 3D data array?
So I'm not sure what word fits best to describe this data, probably "dimension" would be wrong since it may be used for flat samples with 3 features;
but by 3D data I mean some structure in a form of [samples, timesteps, features]. And there are 2 features in eac... |
H: Why is the decoder not a part of BERT architecture?
I can't see how BERT makes predictions without using a decoder unit, which was a part of all models before it including transformers and standard RNNs. How are output predictions made in the BERT architecture without using a decoder? How does it do away with decod... |
H: Importing .ipnyb file from Kaggle into local Jupyter
Total beginner question here, please let me know if it would be more appropriate somewhere else.
I just created my first iPython notebook in Kaggle and I downloaded the ipnyb file. Now I have installed Jupyter locally and want to try working on the same notebook ... |
H: Is it possible to decompose a scalar value to a inter-dependent vector neural network?
My data contains a scalar feature $r$, I found this feature is important for training my deep model. My idea is supposing there is a 3-layer MLP $f(x), x \in \mathbb{R}^{n}$, where $n=1$. It outputs a vector with dimension $m$ wh... |
H: How do I predict survival curves using xgboost?
The xgboost package enables survival modeling using parameter arguments: objective = "survival:cox" and eval_metric = "cox-nloglik".
The predict method for the resulting model only outputs risk scores (same as type = "risk" in the survival::coxph function in r).
How ... |
H: Are parquet files compressed?
Parquet File Format Hadoop. Parquet, an open-source file format for Hadoop. Parquet stores nested data structures in a flat columnar format. Compared to a traditional approach where data is stored in the row-oriented approach, parquet is more efficient in terms of storage and performan... |
H: How to calculate perplexity in PyTorch?
I am wondering the calculation of perplexity of a language model which is based on character level LSTM model. I got the code from kaggle and edited a bit for my problem but not the training way. I have added some other stuff to graph and save logs. However, as I am working o... |
H: What's the best way to train a NER model?
I am trying to do a project using NLP. My goal is to process Cyber Threat Intelligence articles like this to extract information such as actor’s name, malwares and tools used…
To do that I want to use NER. However, there isn’t training data available on the web. So I was wo... |
H: Why is T test reweighting on a word X word co-occurrence matrix so effective?
I am going through Stanford NLP class: http://web.stanford.edu/class/cs224u/
A task in the homework is to implement T-test reweighting on a word X word co-occurrence matrix:
https://nbviewer.jupyter.org/github/cgpotts/cs224u/blob/2019-sp... |
H: How different should discriminator be from generator in GAN
When training a GAN, the generator $G$ strives to fool the discriminator $D$, while $D$ attempts to catch any output generated $G$ and isolate it from a real data point. They grow together training in turns for each epoche.
Assuming $D$ is already an expe... |
H: sklearn.naive_bayes VS categorical variables
In a binary classification, how can I use sklearn.naive_bayes python module to predict the class of inputs with 5 categorical variables (not binary)?
AI: Hot encode the categorical variables and use Bernoulli naive Bayes. Hot encoding is usually the trick one uses in rep... |
H: What is the difference between NLP and text mining?
As discussed with Sean in this Meta post, I thought it would be nice to have a question which can help people who were confused like me, to know about the differences between text mining and NLP!
So, what are the differences between nlp and text-mining?
I have in... |
H: Classification using xgboost - predictions
I was trying to build a 0-1 classifier using xgboost R package. My question is how predictions are made? For example in random forests, trees "vote" against each option and the final prediction is based on majority. As regard xgboost, the regression case is simple since pr... |
H: Neural networks: which cost function to use?
I am using TensorFlow for experiments mainly with neural networks. Although I have done quite some experiments (XOR-Problem, MNIST, some Regression stuff, ...) now, I struggle with choosing the "correct" cost function for specific problems because overall I could be cons... |
H: How can I read in a .csv file with special characters in it in pandas?
I am trying to read in a .csv file containing some data. I only need to read in specific chunks of rows from the file, such as line 15- line 20, line 45-line 50, and so on. However, the file contains text and copy write information like, such as... |
H: How can I dynamically distinguish between categorical data and numerical data?
I know someone who is working on a project that involves ingesting files of data without regard to the columns or data types. The task is to take a file with any number of columns and various data types and output summary statistics on t... |
H: Analyzing customer response
I'm new to ML. I'm taking over a Classification project which involves analyzing data for customers which returned a product and I need to determine the return reason (~10 categories).
This data was captured at the counter, and could include words like: LGTM (Looks good to me) NFF (No f... |
H: What to do with stale centroids in K-means
When I run Kmeans on my dataset, I notice that some centroids become stale in the they are no longer the closest centroid to any point after some iteration. Right now I am skipping these stale centroids in my next iteration because I think those centroids no longer represe... |
H: Classifying survey response text SVM
I have 800 responses to an open-ended survey question. Each response is categorized into 3 categories based on a list of 70 categories. These categories are things like "stronger leadership", "better customer service", "programs", and etc...
My question is, can I use this as a t... |
H: What is the best file format to store an uncompressed 2D matrix?
For what it's worth my particular case is a symmetrical matrix, but this question should be answered more generally.
AI: The most compatible format is surely CSV/TSV. It's text and you can usually Gzip it on the fly with the software package you are u... |
H: Optimizing co-occurrence matrix computation
I am computing co-occurence matrix for a fixed windows size in python using scipy's lil_matrix for storing the counts and computing the counts by sliding the context window over each word and then counting in the window.
Now the code is taking too much time for relativel... |
H: What is a "residual mapping"?
A recent paper by He et al. (Deep Residual Learning for Image Recognition, Microsoft Research, 2015) claims that they use up to 4096 layers (not neurons!).
I am trying to understand the paper, but I stumble about the word "residual".
Could somebody please give me an explanation / defin... |
H: Decompose annual time series in R
I have a time series. Data points are available for each year from 1966 to 2000. Using R, I want to decompose this time series into trend, seasonal and random components. When I run the decompose command, I get the error "time series has no or less than 2 periods". Since my data is... |
H: What model should I use to find a common pattern for a specific user group based on the other dimensions?
I have a big .CSV database of 25k users with various attributes of the last user's activity and events during the past 6 weeks
This is an example of the data:
username (B) (C) (D) ... |
H: What would be the best way to structure and mine this set of data?
http://pastebin.com/K0eq8cyZ
I went through each season of "It's Always Sunny in Philadelphia" and determined the character groupings (D=Dennis, F=Frank, C=Charlie, M=Mac, B=Sweet Dee) for each episode. I also starred "winners" for some episodes. Ho... |
H: NLP - Is Gazetteer a cheat?
In NLP, there is the concept of Gazetteer which can be quite useful for creating annotations. As far as I understand:
A gazetteer consists of a set of lists containing names of entities
such as cities, organisations, days of the week, etc. These lists are
used to find occurrences of... |
H: Autoencoders for feature creation
When using an auto encoder to create non-linear dimensional reduced featires, is it more common to use the output of the network (the prediction of the input features) or to use the weights from the (or 1 of the if there are multiple) hidden layers? If the hidden layer is used, do ... |
H: What's a good machine learning algorithm for low frequency trading?
I'm trying to train an algorithm to copy some of the top traders on various forex social trading sites. The problem is that the traders only trade around say 10 times per month so even if I only look at minute resolution numbers that's .02% of the ... |
H: Filter Data for clustering
I am trying to synthetize clients Data in order to do clustering. My problem is for 1 customer I have severals rows. I would like to synthetize informations to get 1 row per customer. This clustering is about how customers use fidelity program. Here is a picture of my table : By Column (l... |
H: do autoencoders work well for non images?
I have a classification problem for which a feedforward, fully connected neural net works reasonably well (two classes, true positive and true negative rate close to 80%).
I want to get these rates to 90%, and more features is one of the catalysts for improvements I can thi... |
H: On coursera what exactly does Andrew Ng say in videos Lectures 60 & 61 of machine learning?
Model Selection and Train/Validation/Test Sets - Stanford University | Coursera:
At 10:59~11:10
One final note: I should say that in the machine learning as of this practice today, there aren't many people that will do that... |
H: What is the best Keras model for multi-class classification?
I am working on research, where need to classify one of three event WINNER=(win, draw, lose)
WINNER LEAGUE HOME AWAY MATCH_HOME MATCH_DRAW MATCH_AWAY MATCH_U2_50 MATCH_O2_50
3 13 550 571 1.86 3.34 4.23 ... |
H: Data structure design for supporting arbitrary number of columns in table or database
I'm currently working on a sort-of a meta-modeler to build a free web service so that people can input data and run several models on that data.
The task I'm currently struggling is: user needs to enter data column by column, whic... |
H: Inferring Relational Hierarchies of Words
I am new to natural language processing and I have not heard of a problem similar to mine yet. I was wondering if anyone could refer me to a method for solving my problem, or tell me how this problem is referred to in the academic literature, so that I can look for resource... |
H: Improve k-means accuracy
Our weapons:
I am experimenting with k-means and Hadoop, where I am chained to these options for various reasons (e.g. Help me win this war!).
The battlefield:
I have articles, which belong to c categories, where c is fixed. I am vectorizing the contents of the articles to TF-IDF features.... |
H: Analysis of Real-Time Bidding
I'm totally new to the topic of real-time bidding in which I know Machine Learning algorithms are used pretty often.
Can somebody explain me the system in a plain language i.e. a language for a non-technical person?
What is the bidding? Who bids on what? Where does Machine Learning get... |
H: Simple ANN visualisation
TLDR: Please help me understand the graph representation of the network in the image below.
Hi, this is pretty stupid, but I'm just have trouble visualising what I'm actually doing with this neural network.
I've read about neural networks and multilayer perceptrons for some time and I'm jus... |
H: Machine Learning Steps
Which of the below set of steps options is the correct one when creating a predictive model?
Option 1:
First eliminate the most obviously bad predictors, and preprocess the remaining if needed, then train various models with cross-validation, pick the few best ones, identify the top predictor... |
H: Image classification in python
I have a set of images that are considered as good quality image and other set that are considered as bad quality image. I have to train a classification model so that any new image can be said good/bad.
SVM seems to be the best approach to do it. I know how to do it in MATLAB.
But,ca... |
H: How to make k-means distributed?
After setting up a 2-noded Hadoop cluster, understanding Hadoop and Python and based on this naive implementation, I ended up with this code:
def kmeans(data, k, c=None):
if c is not None:
centroids = c
else:
centroids = []
centroids = randomize_centr... |
H: Is parsing files an application of machine learning?
I presently receive files from a device in a semi-csv format. I have a written a simple recursive descent parser for getting information out of these files. Every time the device updates firmware, I have a new version of the parser for the changes the update brin... |
H: Which machine learning approach/algorithm do I choose for path validation?
I apologize for lack of terminology, I'm no computer scientist.
I have a problem of validating paths in a directed graph with complex nodes.
The full description is the following:
I have a decent set (about 1K) of directed graphs;
Each node... |
H: Represent time-series data in much compact form
I have time series data of one month plotted day-wise as
Notice every day follows a different pattern. Now, I want to show this "diversity in pattern" of each day in much compact form in a research paper. What are the different ways/options of representing this in co... |
H: Orange 3 Heatmap clustering under the hood
I have recently used the heatmap widget in Orange 3. All the documentation says is "Clustering (clusters data by similarity)". Is this using hierarchical or k-means or some other type of clustering?
On that note, is there a way to look at the code being run by all the wid... |
H: Markov switching models
What are some reference sources for understanding Markov switching models?
AI: Firstly, for understanding the Markov switching models, a nice knowledge of Markov models and the way they work. Most importantly, an idea of time series models and how they work, is very important.
I found this t... |
H: Knn distance plot for determining eps of DBSCAN
I would like to use the knn distance plot to be able to figure out which eps value should I choose for the DBSCAN algorithm.
Based on this page:
The idea is to calculate, the average of the distances of every point
to its k nearest neighbors. The value of k will b... |
H: t test or anova
I have a pandas data frame of the form:
r1 r2 r3 r4 r5
0 1 12 0 4
1 1 2 9 2
32 5 0 0 0
12 14 3 1 23
0 2 43 5 2
9 3 5 1 1
0 0 0 0 1
1 0 0 0 0
And I want to check if any column: r1, r2, r3, r4, r... |
H: Why do cost functions use the square error?
I'm just getting started with some machine learning, and until now I have been dealing with linear regression over one variable.
I have learnt that there is a hypothesis, which is:
$h_\theta(x)=\theta_0+\theta_1x$
To find out good values for the parameters $\theta_0$ and ... |
H: Distributed k-means in Spark
I want to implement K-means algorithm in Spark. I am looking for a starting point and I found Berkeley's naive implementation. However, is that distributed?
I mean I see no mapreduce operations. Or maybe, when submitted in Spark, the framework actually makes the needed tricks under the ... |
H: How to interpret a decision tree correctly?
I'm trying to work out if I'm correctly interpreting a decision tree found online.
The dependent variable of this decision tree is Credit Rating which
has two classes, Bad or Good. The root of this tree contains all 2464
observations in this dataset.
The most influential... |
H: Should I take random elements for mini-batch gradient descent?
When implementing mini-batch gradient descent for neural networks, is it important to take random elements in each mini-batch? Or is it enough to shuffle the elements at the beginning of the training once?
(I'm also interested in sources which definitel... |
H: What is a Dichotomy?
I am currently reading:
Stephen Jose Hanson: Meiosis Networks, 1990.
and I stumbled about this:
It is possible to precisely characterize the search problem in terms of the resources or degress of freedom in the learning model. If the task the learning system is to perform is classification t... |
H: Doc2Vec - How to label the paragraphs (gensim)
I am wondering how to label (tag) sentences / paragraphs / documents with doc2vec in gensim - from a practical standpoint.
Do you need to have each sentence / paragraph / document with its own unique label (e.g. "Sent_123")? This seems useful if you want to say "what ... |
H: How to make data predictions
As a total beginner I am trying to apply some "predictions" on top of a bunch of csv files which contains house transactions for the last 20 years divided per area. What I would like to predict is the trend of the transactions for lets say the next year for a specific area.
What general... |
H: Gathering the number of Google results from a large amount of searches.
I am trying to build a simple dataset using Google, mainly because it seems like the best option for what I want.
I want to measure fame for a large group of scientists. The quick method is to measure the amount of Google results when searchin... |
H: What is the difference between (objective / error / criterion / cost / loss) function in the context of neural networks?
The title says it all: I have seen three terms for functions so far, that seem to be the same / similar:
error function
criterion function
cost function
objective function
loss function
I was w... |
H: Soccer Field Segmentation
I would like to develop a soccer field segmentation method. For this purpose, I prepared a training image data set and annotated field and non-field pixels. Following is a gr-chromacity plot of all training samples, colored with respect to their labels.
I want to train a classifier for i... |
H: Sort by average votes/ratings
I have a data set that's a dictionary of tuples. Each key represents an ID number and each tuple is (yesvotes, totalvotes). Example:
{17: (6, 10), 18: (1, 1), 21: (0, 2), 26: (1, 1), 27: (3, 4), 13: (2, 2)}
I need to find the max key of the set. I want to assign weights so, for instanc... |
H: Why is there no end user Application, yet?
machine learning is being hyped since the deep neural networks.
It seems to me, that you have to program in order to do machine learning.
But is the process of training data and labeling data is the same of every problem. Why isn't there an Excel like application that enab... |
H: PCA and maintaining relationship with target variable
I'm rather new to PCA and was hoping to have some confusion cleared up. Lets say for example we have a feature matrix that's nx100 and I want to get it down to something a bit smaller, p-dimensions, without losing too much variance.
After applying PCA and recei... |
H: Colouring points based on cluster on matplotlib
I have a set of points where I performed a KMeans classification. How make a plot where the color of the point is based on the cluster they belong?
EDIT: for clarification, having the set of points, I want to use the values of the array generated from KMeans.predict()... |
H: ML packages in R: caret v e1071
I've looked and surprisingly have not found too much discussion on the relative strengths of the caret and e1071 package. From my understanding, these packages perform many of the same ML algorithms. With that in mind, I'm interested in what those practitioners who have experience ... |
H: How do linear learning systems classify datapoints that fall on the hyperplane
How do linear learning systems, such as the simple "closest to the class average" algorithm or SVMs, classify datapoints that fall on the hyperplane?
AI: Linear, binary classifiers can choose either class (but consistently) when the data... |
H: Understanding Reinforcement Learning with Neural Net (Q-learning)
I am trying to understand reinforcement learning and markov decision processes (MDP) in the case where a neural net is being used as the function approximator.
I'm having difficulty with the relationship between the MDP where the environment is explo... |
H: Ignoring symbols and select only numerical values with pandas
In one field I have entries like 'U$ 192,0'. Working on pandas, how I ignore non numerical data and get only the numerical part?
AI: Use str.strip if the prefix is fixed or str.replace if not:
data = pandas.Series(["U$ 192.0"])
data.str.replace('^[^\d]*'... |
H: Left Join with b.key being NULL in R
I am trying to replicate the below sql query in R
select a.*, b.key from Table1 a
LEFT OUTER JOIN Table2 b
on a.key = b.key where b.key is null
I have read through this post however I am still struggling to code my specific case. https://stackoverflow.com/questions/1299871/h... |
H: Analyze performance Poisson regression model on a time series(count forecasting)
I have tried to build a model to forecast the count of a particular variable.The model that was used for the purpose was poisson .Unfortunately ,i don't have enough stat knowledge to analyze the model performance .If somebody can provi... |
H: How do we know Kernels are successful in making data linearly Separable?
When we have linearly inseparable datasets and we are using machine learning algorithms such as SVMs, we use kernels to implicitly map datapoints into a feature space that makes them linearly separable.
But how do we know if a kernel has inde... |
H: Stanford NER - Increase probability for a certain class
I'm new to machine learning so I apologize if this question is silly. I'm using Stanford NER's english 4class classifier with good results. However, since my dataset is mostly focused on organizations, I think the results could be improved if I could boost the... |
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