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Feature Request: Pipelining Outlier Removal · Issue #9630 · scikit-learn/scikit-learn
Yes, #3855, #4143, #4552 and scikit-learn/enhancement_proposals#2 all relate.

I don't see why resample is entirely inappropriate here.

Meta-estimator (almost; untested):

class WithoutOutliersClassifier(BaseEstimator, ClassifierMixin):
def __init__(self, outlier_detector, classifier):
self.outlier_detector = outlier_detector
self.classifier = classifier

def fit(self, X, y):
self.outlier_detector_ = clone(self.outlier_detector)
mask = self.outlier_detector_.fit_predict(X, y) == 1
self.classifier_ = clone(self.classifier).fit(X[mask], y[mask])
return self

def predict(self, X):
return self.classifier_.predict(X)
sklearn  pipeline  meta  estimator  transform  target  sample 
5 days ago by dabana
Bessel’s correction and the dangers of MOOCs | Bits of DNA
Why the denominator for the estimate of variance is n-1 and not n.
statistics  error  estimator 
july 2018 by mark.larios
Cool Backgrounds
About this tool
Cool Backgrounds
After laboring over your latest piece of writing, one of the hardest steps before hitting publish is finding an exciting background image to really showcase and draw attention to your post.
Cool Backgrounds is a collection of tools to create compelling, colorful images for blogs, social media, and websites. Beyond backgrounds, the images generated can be used as 🖥 desktop wallpapers or cropped for 📱 mobile wallpapers.
“How have I worked without a creative tool like this? It makes me feel like a super marketing guru!” Robert Yuen, Head of Growth
For the initial launch, the site exposes five of my favorite background tools from dynamic particles to the ever popular Unsplash. The intention over time is to add more options with this site serving as a curated repository of the best background image tools on the web.
Why did you make this?
While finishing up a gradient generator project CSS Gradient (which launched earlier this year), I unexpectedly noticed the popularity of wallpaper and background images. Digging a bit deeper, I found this huge community of online sites that were curating wallpaper images from the eclectic Deviant Art crowd to the more modern creative commons image sites. While free static images are great, what was missing was a tool that enables non-technical folks to use all the emerging javascript libraries to create unique images of their own. So Cool Backgrounds was born 💥.
Use Cases
With the increasing visual nature of the web, the background images from this site can be used for a plethora of reasons. Listed here are a few ideas to get the creative engine started.
Blog Post Hero Image
The image discovery problem first emerged while working on tutorials for HTML Color Codes. With somewhat dry material like HTML code, it's hard to create a compelling image that represents the actual power of that knowledge. Trianglify.js to the rescue! Utilizing the javascript library, we added our brand colors and generated a high resolution image that looked amazing. To this day we still get random emails asking us how we created that background 😄.
Social Media Banner
Nearly every social media site has a profile banner that lets you showcase an image at the top. Whether you need an image for a Facebook Group, a parody Twitter account, or even yourself, Cool Backgrounds can let you show the world your creative side.
Desktop and Phone Wallpaper
One of the primary reasons folks search for background images is to set them as wallpapers on their computers and phones. As a personal favorite, I'm using the Gradient Topography background in Black and Dark Grey—it sits stealthily on the homescreen of my iPhone.
As a quick sample of a few options availabe on Cool Backgrounds, the following list of images are ready to use for any application. To download, right click and select "Save Image As..."
While Cool Backgrounds is a fine resource for generating images from popular javascript libraries, the real heavy lifting comes from the library authors themselves. When it comes to customer support, Quinn Rohlf from Trianglify.js is incredibly responsive and a really smart guy to boot. Particle.js is developed by Marc Brüderlin with a wonderful API and is being actively maintained. Gradient Topography is a newly minted project by me as a response to the amazing work by the Codrops crew. And of course Unsplash is one of the best internet treasures of all time, built by the former Crew team as a side project.
Oh yea and can't forget CSS Gradient and Rellax.js which is the "cool background" that powers those sliding parallax shapes in the content section of this site!
Side Project Collective
We're  a  group  of  makers  with  a  mission  to  build  a  better  internet_  one  digital  project  at  a  time.  Recently  launched  tools  include  a  gorgeous  retirement  estimator  Investment  Calculator  and  a  seamless  way  to  count  words  with  Word  Counter.  from iphone
may 2018 by kgiverson
Finlite - Estimator and Contractor Guide
used to roughly estimate costs of running rigid metal conduit at BGT
bgt  bosch  estimator  construction  materials  pricing 
july 2017 by aaronbeekay
Frequently Asked Questions — scikit-learn 0.18.1 documentation
Firstly, many estimators take precomputed distance/similarity matrices, so if the dataset is not too large, you can compute distances for all pairs of inputs. If the dataset is large, you can use feature vectors with only one “feature”, which is an index into a separate data structure, and supply a custom metric function that looks up the actual data in this data structure. E.g., to use DBSCAN with Levenshtein distances:
dbscan  distance  estimator 
june 2017 by pskomoroch

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