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H: What's the difference of Symbolic translation approach and statistical translation?
Based on what I know, symbolic computing is based on hard rules in the code. Statistical translation is based on statistic and probabilities. If so, could you give an easy to understand example to demonstrate this difference? If it ... |
H: Does bias have multiple meanings in Data Science?
What are the meanings of Bias?
And is Under fitting, which is used in machine learning contexts, the same as "Bias"?
I have faced biased data in sampling in statistics but it seems this is a different thing to bias in learning concepts.
I have heard that some data... |
H: Gradient boosting vs logistic regression, for boolean features
I have a binary classification task where all of my features are boolean (0 or 1). I have been considering two possible supervised learning algorithms:
Logistic regression
Gradient boosting with decision stumps (e.g., xgboost) and cross-entropy loss
... |
H: Correct order of operations involved into Dropout
Suppose we have CNN with any hidden layer with activation followed by dropout layer. What is the correct precedence of activation and dropout operation if dropout implementation is inverted dropout and CNN mode is training mode? Do I need to compute activation in th... |
H: Which functions neural net can't approximate
I read somewhere on the StackExchange that a neural network can't approximate the Pi number as a function of circles length and radii. Maybe this is an incorrect example or wrong information. Help me to understand.
What about the sum or multiplication of any arbitrary nu... |
H: Why does a randomly initialised convolution kernel correspond to an edge detector?
In this nice tutorial about CNNs, the authors build a single-layer CNN. The initial convolution weights are set randomly, according to a uniform distribution.
By the end of this scetion, the authors note that the randomly initialise... |
H: Feature importance with high-cardinality categorical features for regression (numerical depdendent variable)
I was trying to use feature importances from Random Forests to perform some empirical feature selection for a regression problem where all the features are categorical and a lot of them have many levels (on ... |
H: Why not train the final model on the entire data after doing hyper-paramaeter tuning basis test data and model selection basis validation data?
By entire data I mean train + test + validation
Once I have fixed my hyperparameter using the validation data, and choose the model using the test data, won't it be better ... |
H: How to (better) discretize continuous data in decision trees?
Standard decision tree algorithms, such as ID3 and C4.5, have a brute force approach for choosing the cut point in a continuous feature. Every single value is tested as a possible cut point. (By tested I mean that e.g. the Information gain is calculated ... |
H: Semi-gradient TD(0) Choosing an Action
I am trying to write an optimal control agent for a simple game that looks like this:
The agent can only move along the x-axis, and has three actions available to it: left, right, and do nothing. A random number of falling rocks are spawned at arbitrary positions along the to... |
H: Clustering Multiple Networks
I'm looking for methods of Community Detection in networks. For example if I have a network of 100 people (each node is a person), how can I cluster nodes? What would be the best approach for grouping these People? I know this question is rather open, but I'm just looking for a nudge in... |
H: Adding document vector doc2ec to seq2seq model
In general we use word2vec for word embedding in seq2seq model, is it possible to add the document vector from Doc2vec with the input words , I mean using the tag of the document as a word and its vector for emending : the picture will explain mu point a view
default... |
H: Item Similarity with Location Feature
I'm currently learning about Collaborative Learning and Content-based Recommendation.
One of the main things that is discussed in both methods is about calculating similarity between two users or two items. Commonly, similarity between two entity (each represented by a vector) ... |
H: BI vs Data Science. Looking for a difference in definitions
can someone please tell me the difference between a BI trendline, and a linear/exponential regression?
When explaining this to a hardcore BI person, what can be used to mark the difference? Thanks.
AI: Any difference in regression models can be reduced t... |
H: Detecting patterns from a collection of data
I have a collection of data for a multiplayer game (2000 games, 10 players each). I would like to create clusters from this data, each containing the ids of 3 players that had played against each other.
AI: You can use Python networkx module to find all 3-cliques:
import... |
H: How ANN is used for classification?
I am reading about artificial neural networks and it is said that ANN is used for prediction after training with training data. It is also given that ANN is used for classification.
Say I have data consisting of input as ($\theta$, sin($\theta$)) and output as -1 if it is in uppe... |
H: Regular expression in python -
I want to extract the values of the below text
Pafient Name : Thomas Joseph MRNO : DQ026151?
Doctor : Haneef M An : 513! Gandar : Male
Admission Data : 19-Feb-2V'3‘¥T12:2'$ PM Bill No : IDOGIII.-H-17
Discharge Date : 22-Feb-20$? 1D:5‘F AM Bill Dale : E2-Feb-2017
extract only the value... |
H: Self adjusting CNN network
I am currently trying to build a self adjusting network, such that given any number of inputs, should always provide an output of shape (15,145)
The network structure is pretty simple and looks like this:
inputs = 36
list_of_input = [Input(shape = (45,5,3)) for i in range(inputs)... |
H: Is GridSearchCV computing SVC with rbf kernel and different degrees?
I'm running a GridSearchCV with a OneVsRestClasssifer using SVC as an estimator. This is the aspect of my Pipeline and GridSearchCV parameters:
pipeline = Pipeline([
('clf', OneVsRestClassifier(SVC(verbose=True), n_jobs=1)),
])
parameters... |
H: Limitations of Perceptron
If you are allowed to choose the features by hand and if you use
enough features, you can do almost anything.For binary input vectors,
we can have a separate feature unit for each of the exponentially many
binary vectors and so we can make any possible discrimination on
binary inp... |
H: The danger of "amplifying noise"
A data scientist cautioned me against "just amplifying noise" in a data analysis. What did he mean? Can you explain and/or point to resources explaining the problem?
AI: There is very little information in this question. I will try to answer this in the most generic sense. Let's sta... |
H: I have n dimensional data and I want to check integrity, can I downgrade to 2 dimensional feature space via PCA and do so?
Say I have n dimensional data samples. I want to check the integrity of the features, if they are good representation of the respective classes, i.e. these features are good or not.
My plan is:... |
H: Which machine learning technique for product ranking/scoring
I am trying to identify a ML technique to score products based on the number of times the product was "viewed", "clicked" and knowing the "cost per click" for each product. Given the product ID and category ID, how can I proceed to score each product?
I a... |
H: How to deal with time series of multi-source energy in order of classifcation?
I would like to do classification of multi-source energy (wind/solar/teg) repersented in a time series data.
My questions are :
1- What are the most relevent feature that I should chose to do the classification (statistical ones (kurto... |
H: ML technique to predict next online
I want a direction for ML technique to predict the next time you will be online in chat app
My table contains; user id, timestamp & status
status is a categorical variable (online, composing, offline), I'm saving a row for each status change which means user online, maybe writes ... |
H: Is there a way to calculate value from a radar (spider) chart?
So I am currently working on a project for "sales people". Essentially, the user is giving us a plethora of information related to deals they are trying to win. We have data related to the price of the deal, margin of the deal, number of people working ... |
H: How to build a model which can predict the probability of an event based on a set of timeseries data?
I am trying to build a deep learning neural model using keras and tensorflow which can predict if a certain event will occur based on a set of timeseries data and some fixed data together . For example:
For a given... |
H: Abbreviation Classification using machine learning
I would like to classify abbreviations using machine learning. For example:
I have watermel. and I ask for user what is watermel.(my application context is about food). Then He classify as watermelon.
In other time, If Other user insert waterme. Is It exist a way t... |
H: Deriving backpropagation equations "natively" in tensor form
Image shows a typical layer somewhere in a feed forward network:
$a_i^{(k)}$ is the activation value of the $i^{th}$ neuron in the $k^{th}$ layer.
$W_{ij}^{(k)}$ is the weight connecting $i^{th}$ neuron in the $k^{th}$ layer to the $j^{th}$ neuron in th... |
H: Improving classifier performances in R for imbalanced dataset
I have used an "adabag"(boosting + bagging) model on an imbalanced dataset (6% positive), I have tried to maximized the sensitivity while keeping the accuracy above 70% and the best results I got were:
ROC= 0.711
SENS=0.94
SPEC=0.21
The results aren... |
H: Why use both validation set and test set?
Consider a neural network:
For a given set of data, we divide it into training, validation and test set. Suppose we do it in the classic 60:20:20 ratio, then we prevent overfitting by validating the network by checking it on validation set. Then what is the need to test it ... |
H: Eliminate input in gradient by clever choosing of cost function in neural networks
In http://neuralnetworksanddeeplearning.com/chap3.html
The author explains that for for a single neuron in neural net, by choosing cost function as cross entropy we can eliminate the derivative of activation function in the gradient ... |
H: Predicting probability from scikit-learn SVC decision_function with decision_function_shape='ovo'
I have a multiclass SVM classifier with labels 'A', 'B', 'C', 'D'.
This is the code I'm running:
>>>print clf.predict([predict_this])
['A']
>>>print clf.decision_function([predict_this])
[[ 185.23220833 43.62763596 ... |
H: How are the positions of the output nodes determined in the Kohonen - Self Organizing Maps algorithm?
In the Cooperative stage of Kohonen's SOM, the neighborhood for a winning neuron(output node). In most cases, the neighborhood function happens to be the Gaussian Function.
For example,
$$h_j,_i = exp(-d_j,_i^2/2*\... |
H: Are there any rules for choosing the size of a mini-batch?
When training neural networks, one hyperparameter is the size of a minibatch. Common choices are 32, 64, and 128 elements per mini batch.
Are there any rules/guidelines on how big a mini-batch should be? Or any publications which investigate the effect on t... |
H: Algorithm for finding best juice combinations
I am making a fun experiment in which a machine will mix different percentages of three juices – orange, apple and grape. After each mix is dispensed, a participant will taste the juice and rate it on a numeric scale, a score from 1 to 7.
Using the data collected, I wou... |
H: Elastic Regression fitting good mean and bad variance
So, I'm kinda new to machine learning and I was trying to predict the monthly sales of a business using a set of features and using a sliding window of the past sales of 12 months.
I used some algorithms to do it, including linear/polynomial regression, lasso/el... |
H: Classification followed by regression to handle response variable that is usually zero
I have a data set consisting of a bunch of predictors (mostly unbounded or positive real numbers) and a single response variable that I wish to predict. The response is typically exactly zero -- around 90% of the time. I have tri... |
H: Python package for machine-learning aided data labelling
In a lot of cases unlabelled data needs to be transformed to labelled data. The best solution is to use (multiple) human classifiers. However, going to all the data by hand (i.e. in text-mining or image-processing) is often a daunting task. Is there software ... |
H: How to Choose a Sample for Multiply Classifiers
I've got a dataset of 1.5 million and am looking to train 7 different classifiers -- for each classifier I have up to 10 classes to predict. The total sample has 20K text features (more if I include bigrams). Like most distributions of text features, only 20% of them ... |
H: Understanding how distributed PCA works
As part of big data analysis project, I'm working on,
I need to perform PCA on some data, using cloud computing system.
In my case, I'm using Amazon EMR for the job and Spark in particular.
Leaving the "How-to-perform-PCA-in-spark" question aside, I want to get an understandi... |
H: Neural networks - adjusting weights
My question would be about backpropagation and understanding the terms feedforward NN vs backpropagation. I have two questions really:
If I understand correctly, even a feedforward network updates its weights (via a delta rule for example). Isn't this also backpropagation? You h... |
H: Can I create a word cloud of crowdfunding donors using word cloud?
I have a table like this:
FirstName SecondName Amount
Lorenzo Perone 100
Mario Rossi 25
... ... ...
I'd like to create a "word cloud" using "Amount" as weight, is it possible using the "word c... |
H: How to train model to predict events 30 minutes prior, from multi-dimensionnal timeseries
Experts in my field are capable of predicting the likelyhood an event (binary spike in yellow) 30 minutes before it occurs. Frequency here is 1 sec, this view represents a few hours worth of data, i have circled in black wher... |
H: Simple Time Series Prediction
I have a data set like this. Here the first column is date, the second column is Temperature, third one is humidity, fourth and fifth column are two other boolean data. I have data of 6 years like this.
2010-01-01,25.6,59,0,1
2010-01-02,25.6,60,0,1
2010-01-03,24.2,45,1,1
2010-01-04,26.... |
H: Creating an Artifical Neural Network that produces a set of possible outputs
I'm new to machine learning, and was working on creating an ANN which would classify each observation to a certain value. I have worked primarily with the sigmoid function up to this point to get the probability of an observation (true/fal... |
H: Does the SVM require lots of features most of the time?
So I know about the curse of dimensionality (too many features too less data).
Say I have a 3000 sample dataset, would 3 features be too less?
AI: So I'll post an answer to my own question. For anyone who comes across this post during the feature selection / M... |
H: Using random forest to select important variables & then putting into logistic regression?
I was wondering does it make sense to use random forest to select most important variables then put into logistic regression for prediction? I think that it might not make sense because what's important for random forest migh... |
H: How can I identify the most predictive factors?
I've been playing around with bagged trees and random forests. How can I tell what factors most influenced the categorization? Will scikitlearn just spit it out, or is it trickier than that?
AI: It basically lies within the fitted object.
model.fit(X, y)
importances ... |
H: Is there a way to measure the "sharpness" of a decision boundary of a CNN?
It is commonly seen as something bad if the decision boundary of a neural network is too sharp, meaning if slight changes in the input change the class prediction completely.
Given a trained CNN, is it possible to measure / calculate the "sh... |
H: Machine learning learn to work well on future data distribution?
This is based on my limited machine learning scope and experience, so correct me if I'm wrong. Many of the currently used machine learning models (SVMs, boosted trees, DNNs) work under the assumption that the training, validation and test data sets sh... |
H: how to do the imputation for categorical feature with a missing rate?
I have a dataset containing a categorical feature with a missing rate 95%. What value can replace the missing cells? Or drop this feature?
AI: You can turn it into a one-hot encoded feature with an added class of 'Missing', depending on the cardi... |
H: Same TF-IDF Vectorizer for 2 data inputs
I am trying to work on Dataset released by quora, to identify if Question1 has similar intent as of Question2
The dataset looks like:
id|question1|question2|is_duplicate
0|What is the step by step guide to invest in share market in india|What is the step by step guide to in... |
H: What is the difference between LeakyReLU and PReLU?
I thought both, PReLU and Leaky ReLU are
$$f(x) = \max(x, \alpha x) \qquad \text{ with } \alpha \in (0, 1)$$
Keras, however, has both functions in the docs.
Leaky ReLU
Source of LeakyReLU:
return K.relu(inputs, alpha=self.alpha)
Hence (see relu code)
$$f_1(x) = \... |
H: Does the input data representation matter while training CNN for speech recognition?
I am currently doing pattern recognition on spectograms of audio files using convolutional neural networks.
The spectograms are made using matplotlib cm.jet colormaps. Problem with this color map is that it auto ranges its colors ... |
H: using classification when there is no dataset + guidance
i am working on my final year project that is a social network. Based on user interest, i have to add him in groups based on area he lives in, age group, interest type, gender and some other features.i have to use machine learning to predict in which group sh... |
H: Anomoly detection method selection
I need to decide between SVM (One-Class Support Vector Machine) and PCA (PCA-Based Anomaly Detection) as anomaly detection methods. Azure ML is used and provides SVM and PCA as methods - hence the choice of 2 possible methods.
Does anyone have suggestions or a defined process for ... |
H: Why predicted proababilities from this binary classifier does not sum up to 1?
I have a C5.0 model that is trained to predict binary class (C1/C2) on a dataset with 20 features. The model is configured to perform boosting (10 trials) and it has a miss-classification cost function (100:1 where 100 is the cost for mi... |
H: Unstable accuracy of CNN - When should I stop training?
I'm using caffenet for fine-tuning.
I'm doing cross validation (15 vs all) with a very small data set of about 250 images. I'm testing every 10 iterations (~2 epochs). My batch size is 50. With some sets I'm getting very unstable accuracy - Can jump from 70% ... |
H: Regression yields much smaller standard deviation and the mean is off, what could be wrong?
I'm modeling a regression problem. An initial attempt yields the following:
labels.mean(): 0.00018132978443886167
labels.std(): 0.013450786078937208
predictions.mean(): 0.0005549060297198594
predictions.std(): 0.00430255476... |
H: What tools do you use to clean corrupt data?
Customer often send currupt data for analysis. I spent a lot of time in cleaning the data or waiting for a correct dataset.
Can you recommend a tool that can handle the most common curruptions (eg. wrong set quotes)...
AI: Weka has built in preprocessing techniques
Also... |
H: Number of outputs exceeds the number of classes in the training set
I have to build a classifier that classifies samples to one of thirteen classes, but the training dataset I have contains only 10 classes (the dataset is not balanced and some classes does not have any sample)
Is it right to build a Neural network... |
H: How to use an existing model as in input into a new model
We have a click-model which is currently being used for search ranking in production, and I want to create a new model which takes the old model click probability as one input and adds some other variables in too. The problem is that training data will posit... |
H: Any Machine Learning algorithm to know a yes/no answer?
Any Machine Learning algorithm to know the meaning of sentences? Specifically, I have sentences like, "we do not allow managers to trade derivatives", "We do not have policy on hedging", "our policy do not permit trading on stock", "trading is not allowed"... ... |
H: Feature selection in R too large dataset
I'm doing credit risk modelling and the data have large number of features.I am using boruta package for feature selection. The package is too computationally expensive, I cannot run it on the complete training dataset. What i'm trying to do is take a subset of the training ... |
H: Classify ciphertext vs. plaintext
I'm attempting a rather simple exercise in machine learning and trying to classify samples of text as either plaintext or ciphertext (encrypted).
Here are two samples:
Plaintext: This is a sentence in plaintext which any human person can read
Ciphertext: 5oXbLiEZbMUgOOdYy+q4+rsDaq... |
H: What are the differences between IBM BlueMix and IBM Data Science Experience?
This may seem like a silly question, but as I am going through the documentation for both services it is difficult to disentangle what each does, specifically. From what I've gathered
BlueMix is essentially an all-in-one cloud platform f... |
H: Does MLP always find local minimum
In linear regression we use the following cost function which is a convex function:
We Use the following cost function
in logistic regression because the preceding cost function is not convex whenever the hypothesis (h) is logistic function. We have changed the equation of cos... |
H: What can i do after a PCA with the results?
After performing a PCA and studying the proceeding i ask myself what the result is good for in the next step. From the PCA i learned how to visualize the dataset by lowering the dimension, i got handy new vectors to describe the members of the population in a more efficie... |
H: sklearn select N best using classifier
pretty simple question here but just can't seem to find the answer in the normally great documentation for sklearn.
I am working with binary classifiers, but we can just assume i am using LogisticRegression, and I was wondering if there is a general way to have the classifie... |
H: Number of features vs. number of samples : if small sample size is sufficient, why take large number of samples?
As a newbie, I am a little confused. I have a dataset for binary classification with 11 features and 102 sample data. I have seen in most places (e.g., kaggle competions), the dataset may have hundreds o... |
H: What is a LB score in machine learning?
I was going through an article on kaggle blogs. Repeatedly, the author mentions 'LB score' and 'LB fit') as a metric for effectiveness of machine learning (along with cross validation (CV) score).
With a research for the meaning of 'LB' I spent quite a bit of time, I realised... |
H: How will a rotation matrix affect contestants in machine learning contests?
Machine Learning contests like Kaggle usually layout the machine learning task in a human-understandable way. E.g. they might tell you the meaning of the input (features). But what if a Machine Learning contest doesn't want to expose the me... |
H: R, xgboost: eval_metric for count:poisson
I wonder what are the recommended eval_metrics for count:poisson as objective in xgboost in R?
AI: This is from XGBOOST documents:
“poisson-nloglik”: negative log-likelihood for Poisson regression.
You might want to go and read more about poisson n loglikelihood.
Here is a ... |
H: How to remove columns in Transformer function in Pipeline?
I already used a custom transformation function in a scikit-learn pipeline. In this function I only added features to my data frame. It works great.
Below is a working example:
import pandas as pd
import numpy as np
from sklearn.pipeline import Pipeline
fro... |
H: how to train tensorflow chat application on updated dataset everyday
I have created chatbot on Cornell movie dataset and it's working fine. I have trained chatbot application up to global step 330000. I am using tensorflow library. I am using ||source|| chatbot. I am also receiving output fine. Then I created this... |
H: What does images per second mean when benchmarking Deep Learning GPU?
I've been reviewing performance of several NVIDIA GPU's and I see that typically results are presented in terms of "images per second" that can be processed. Experiments are typically being performed on classical network architectures such as Ale... |
H: Pull data from R and set lines to ignore
I am trying to pull data from my .csv file. I am using this command:
mydata[mydata$Model_Data>3.0,c("Model_Data","Date")]
As you can see from the results below, it is counting ALL instances, however, I wish to set this to a 64 line ignore upon first matching instance. How... |
H: What are stovepipes?
I am reading the book The Data Warehouse Lifecycle Toolkit by Ralph Kimball. I come across the term Stovepipes fairly often. After doing some research I read that Stovepipes are when you don't have conformed dimensions to link data marts. This short description was all I could find every other ... |
H: Confidence intervals for binary classification probabilities
When evaluating a trained binary classification model we often evaluate the misclassification rates, precision-recall, and AUC.
However, one useful feature of classification algorithms are the probability estimates they give, which support the label pred... |
H: Advice on the learning resources for deep learning
Which is better for beginner in machine learning: The deep learning book written by Yoshua Bengio or the videos and notes in CS231n from Stanford?
AI: http://neuralnetworksanddeeplearning.com/
http://www.deeplearningbook.org/
They are the two very popular online f... |
H: Feature Extraction from Convolutional neural network (CNN) and using this feature to other classification algorithm
As in this, the author is using CNN to extract features of the images, and then doing SVM for further analysis. My question is how to extract features in CNN?
E.g., here is a CNN code I'm using:
%matp... |
H: Issue with backpropagation using a 2 layer network and softmax
I have a simple neural network with one hidden layer and softmax as the activation function for the output layer. The hidden layer uses various activation functions since I am testing and implementing as many of them as I can.
For training and testing ... |
H: Different number of features in train vs test
I'm doing the titanic exercise on kaggle and there is a categorical Cabin attribute that has a lot of different strings: C41, C11, B20 etc. (about 100).
To be able to train my model I'm converting it to numerical attributes (using pandas get_dummies()). So in the end I ... |
H: Best way for data preparation to have accurate prediction
I'm trying to experiment if an opportunity will win or lose in Azure Machine Learning studio. However, am still in Data preparation method.
In my Data base I have opportunity table and products table.
For example, one opportunity has multiple products. Shoul... |
H: What happens when you have highly correlated columns in a dataset?
I am doing a regression model. And I was wondering what would be the consequence if we have two or more Highly correlated columns in the dataset? Is that something that can decrease the accuracy of the model?
Answering this question would help decid... |
H: Why CNN doesn't give higher accuracy over simple MLP network? [From Keras examples]
I'm still new to machine learning and just came across powerful deep learning library, Keras.
I've read Keras document and tried few Keras examples on Github here. I've also studied some basic knowledge and concepts of deep learning... |
H: Are deep - learning toolkits targeted for certain areas or all-purpose tool kits?
Are any of the open deep learning toolkits targeted to certain areas, or a all toolkits all purpose toolkits, meaning it is a blackbox for deep learning.
My question comes in regards to Microsoft's CNTK which seem to contain examples... |
H: Using the cosine activation function seems to perform very badly
I have created a neural network to classify the MNIST handwritten numbers dataset. It is using softmax as the activation function for the output layer and various other functions for the hidden layer.
My implementation with the help of this question s... |
H: Where to find statistically relevant documentation of common Python packages?
I am trying to entice my lab to transition from Matlab and R to Python. The main objection at this point seems to be that Python's analytical libraries are not sufficiently well documented. Given how prolific Python is, I suspect that suf... |
H: Updating One-Hot Encoding to account for new categories
My question is focused around how to appropriately update an encoded feature set when a new category is introduced by the test data. I use the data in logistic regression and I know it is not a 'live' model (i.e. gradient descent is performed whenever new data... |
H: clustering multivariate time-series datasets
I am new to clustering.i have data from quality testing of an automobile manufacturing company.
I have 100000 datasets.each dataset has 4 variables force, voltage, current, distance. each variable is a continuous time-series with 8000 data points each(1 to 17000 millisec... |
H: Using word2vec with mixed language data
I scraped my Facebook chat history and wanted to try out some basic machine learning stuff with word2vec. However, the data has all sorts of stuff - links, emoji, Cyrillic alphabet, etc. Even if I manage to clear some of those, would it be possible to process the Cyrillic alp... |
H: How can you map the exceedance of a threshold into an activation function of a Neural Network?
I am totally new to Artificial Neural Networks. Let’s say that the model you are trying to turn into an artificial neural network has an output that is triggered only by the exceedance of a threshold: $y\geq y_{1}. $There... |
H: Predicting car failures with machine learning
I want to start with machine learning with a small prediction problem but I'm not sure I chose the right approach. I want to make a program that gets data of mechanical failures on cars (manufactured time, failure time, reason, and different characteristics of the car).... |
H: Count the frequncy of words in a cell of a column in a series
I want to calculate the frequency of the words in obama['text'] (obama is the variable where i have stored this series element ) in a dictionary and store it in another column . Without using Counter library , how do i do that . The data is in this form... |
H: h2o, different stopping metric leads to different optimal for hyperparameters
I want to choose the "optimal" hyperparameters for gbm. So I run the following code using the h2o package
# create hyperparameter grid
hyper_params = list(ntrees = c(10,20,50,100,200,500),
max_depth = c(5,10,20,30),
... |
H: What is the purpose of setting an initial weight on deep learning model?
I'm now learning about deep learning with Keras, and to implement a deep learning model at Keras, you set the initializer to set its initial weights on.
from keras.models import Sequential
from keras.layers import Dense
model = Sequential()
mo... |
H: Always overestimate
I have a regression use case where I am supposed to estimate a value based on 3-4 features. Using random forest, I was able to get ~20% error. However, I have a constraint now. I can overestimate but not underestimate. So, at the cost of improving the error I am allowed to overestimate. What is ... |
H: Calculating mean of data frame inside a series object
I have a data frame with following structure:
df.columns
Index(['first_post_date', 'followers_count', 'friends_count', 'last_post_date','min_retweet', 'retweet_count', 'screen_name', 'tweet_count', 'tweet_with_max_retweet', 'tweets', 'uid'],
dtype='objec... |
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