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What our customers say about pdfFiller
See for yourself by reading reviews on the most popular resources:
Easy to use, a little misleading on the web site "try for free" and then it wants to charge me to save / print, but live chat was quick and the chat agent (Anne) was awesome and provided me a 7 day free trial so I can see if this will be worth the subscription. Hats off to the chat agent, awesome customer service, GIVE her a RAISE! LOL
2014-07-22
This program worked for me when I had to do a state specific purchase & sale agreement/real estate. All six signers lived in different states and so had to digital sign. Easy to walk them through it.
2015-08-06
First time, so experiencing a few problems learning your system. Need to spend time learning how to make it work best for me. Will just have to figure it out for myself.
2017-10-10
I really like this, I am using it more than I thought I would. It has made everything very convenient. I also like the fact that the program remembers things that I've previously typed. It saves time for sure!
2017-12-23
A very useful product, although a bit tricky (complex) to work with. I don't fill out enough PDFs to make a subscription worthwhile, even at the discounted 75%-off rate. Thank you for allowing me to try it!
2018-11-01
so far so good, very easy to use. The only issue is I can not verify my office # as I do not use a CELL phone. CAnnot receive SMS text to verify my tel#
2019-05-27
PDF Filler Signature function is great
PDF Filler is pretty good, the ability to edit pdf's is always good but I have found the Signature copy function particularly useful over the standard PDF tools.
2020-02-12
Convenient, Easy, and Potentially Free!
I edit a lot (A LOT) of PDF documents. I love that I can edit, fill, sign from anywhere - on the go, on my phone, in the car, in the hotel. I can get it done and quickly. One of my most used tools hands down.
I would like to see the website redesigned to be slightly more user friendly.
2019-03-13
EFFICIENT AND PROFESSIONNAL
AMAZING SERVICE, i use their services for my wine list at work, works perfectly, and also customer service is great! i made a mistake on my subscription, Paul helped me from their alive chat straight away and refunded me within hours. highly recommended!
2021-12-18
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What is the best feature selection method?
There is no best feature selection method. Just like there is no best set of input variables or best machine learning algorithm. At least not universally. Instead, you must discover what works best for your specific problem using careful systematic experimentation.
What is filter method in feature selection?
Filter Methods are generally used as a preprocessing step. The selection of features is independent of any machine learning algorithms. Instead, features are selected on the basis of their scores in various statistical tests for their correlation with the outcome variable.
What is wrapper method in feature selection?
Wrapper Methods: Definition Wrapper methods work by evaluating a subset of features using a machine learning algorithm that employs a search strategy to look through the space of possible feature subsets, evaluating each subset based on the quality of the performance of a given algorithm.
What is feature selection and filtering?
Feature selection is the process of reducing the number of input variables when developing a predictive model. Filter-based feature selection methods use statistical measures to score the correlation or dependence between input variables that can be filtered to choose the most relevant features.
How do you do feature selection?
Feature Selection is the process where you automatically or manually select those features which contribute most to your prediction variable or output in which you are interested in. Having irrelevant features in your data can decrease the accuracy of the models and make your model learn based on irrelevant features.
Can decision tree be used for feature selection?
For ensembles of decision trees, feature selection is generally not that important. During the induction of decision trees, the optimal feature is selected to split the data based on metrics like information gain, so if you have some non-informative features, they simply won't be selected.
How do you do feature selection using random forest?
Prepare the dataset. Train a random forest classifier. Identify the most important features. Create a new 'limited featured' dataset containing only those features. Train a second classifier on this new dataset. Compare the accuracy of the 'full featured' classifier to the accuracy of the 'limited featured' classifier.
How is feature importance calculated in random forest?
Feature importance is calculated as the decrease in node impurity weighted by the probability of reaching that node. The node probability can be calculated by the number of samples that reach the node, divided by the total number of samples. The higher the value the more important the feature.
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