Do people say

English sentences with fitting data in context,

4 exact matches

We don't get all that excited about models that are only approximately correct; there is something boring and non-fundamental about simply fitting data to some approximate model, compared to figuring out something deep about how the universe actually works!
source: Redditshow contexthide context

There are enough dissenting voices, ill-fitting data and deficiencies in studies for me to have serious doubts about both the prevalance and effects of obesity, particularly when we talk about people at the lower end of what is now considered obese (a definition category which has expanded quite dizzily over the last 20-30 years).
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I believe this process is fundamentally different from fitting data to a mathematical model in an engineering or financial situations.
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It's one thing to be interested in supernovas and black holes while seeing a documentary, or the spookiness of quantum mechanics, but it's another thing to spend ours in lab doing experiments and fitting datas, or maybe spending days trying to understand a simple equation and/or spend pages and hours solving one "simple" problem.
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Estimates from model fitting to data suggest in nature efficiencies vary from about 2-60%, with 10% being a decent rule of thumb, on average.
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The problem is all they have done is create a curve which does an excellent job at fitting past data.
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I don't know about feasibility, since finding a strong generalization moving forward is always more difficult than over-fitting historical data, but there is /r/algotrading if you'd like to give it a try.
source: Reddit

Guess I have to dig up some old course material on fitting my data to a model, I'm pretty sure that was dealt with in a statistics course I once did..
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You're just curve-fitting price data it sounds like - no fundamental data and no grasp on return factors or relevant academic studies (at least you haven't demonstrated any).
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I'm sure I am guilty of fitting the data to my theory.
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In addition, there are some issues when fitting observational data in particle physics, kinematic reflections, and in order to avoid detection of 'false particles' they have created a rule that a particle needs to be seperated from the background noise by 5 sigma, which is pretty tight.
source: Redditshow contexthide context

The approach is probably over-fitting the data extremely.
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A couple of days ago I played around with fitting polynomials to data, to see if I could use it to extrapolate trends.
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What I mean by 'fitting the evidence' is make up a story that fits the established phone calls and make up a story on why he was where the cell phone data says he was.
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Importing data from old, unreliable, and often times perplexing storage formats is harder, and often more painful then fitting 4 dicks up your ass at once.
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The scale is not properly fitting to this data.
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The only thing I would add is is that there's a lot of data players play with in EVE Online, from the player-run markets to ship fitting to mass calculations for wormholes and more.
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Then extrapolates the trendlines and makes some predictions based on what could be done with larger values for all of these capabilities, with said larger values being X at time Y base on curve fitting to existing data.
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I was not able to find the data they were fitting to.
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In short they're fitting a gamma dist presumably because its a good fit in the "middle", but not fitting well near the bounds (the upper bound switched from a long tail to a short tail as I'm guessing more data came through, and we know the pdf of the gamma distribution near 0 isn't plausible).
source: Redditshow contexthide context

Yes the tracking provides useful data for fitting and fine tuning technique but even you seem to thing few golfers have technique which is consistent enough shot-to-shot to make that level of analysis have any practical value during actual play.
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With this combined, data not fully fitting its box, and then putting that partially filled box on the stack, it is possible to rearrange the stack to execute different things because the boxes were empty.
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If you're not suggesting that Jay was fitting his NVC interview to the cell data, then the objection is just a non-sequitur.
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Surely you're not suggesting he was fitting his NVC interview to the cell data and somehow getting it wildly wrong?
source: Reddit

Whenever new data comes out that doesn't match their predictions, they draw a new line fitting to the previous data plus the new data, and try again.
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Good luck passing with data results that likely will be skewed just by the questions being confusing and not fitting to anybody's actual use case
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Hmm, listing the high and low sales would maybe show that spread, altho the real problem is just fitting all that data onto the table.
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Two huge issues are data-mining bias and curve-fitting.
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A custom Android app receives the raw data and calibrates it, by plotting manually inputted blood test strip results vs raw sensor numbers, and best-fitting a relationship line.
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If you're looking the corporate route, data analyst is a very fitting position for someone with a math background.
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Assuming you are fitting inside (Winter most places) The launch monitor data will only get you so far.
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But, don't scorn data-fitting unnecessarily.
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For a photographer the technical data of an IPS panel is much more fitting, than using a TN screen.
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If you really thought you are just fitting a model to the data, science would never become predictive.
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January 28th is International Data Privacy Day, a fitting time to host the first in what we hope will be an ongoing series of Privacy Lab Meetups in the Bay Area.
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After all, if you over-fit on the training data, the theory goes, you'll hopefully do worse on the test set, since you haven't trained on that, and over-fitting usually produces a nonsense model.
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Even fitting his story to the Police's misunderstandings of the Data.
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So, in essence, the fitting the set with the data is not applicable to quantum physics because they're creating the set before the data points are even collected through mathematical theories.
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Put simply, linear fitting is all about minimising how much your data points deviate from your fit.
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Why would fitting a line to this data be in any way meaningful?
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Well I'm pretty sure the pokemon fitting into the pokeball deal is that the pokemon is transformed into data in the form of light, and the inside of the pokeball is essentially an endless mirror that just bounces it endlessly til the mon is sent back out.
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Come to think of it, I don't think I've ever actually demoed boots, partially because any boots that even come close to fitting my ankle are usually so painfully tight elsewhere, trying to ski them wouldn't really yield much data aside from THIS FUCKING HURTS.
source: Reddit Warningshow contexthide context

Today I finally finished writing the overhead necessary to get it to analyze any collection of files without any constraints on the ordering, naming schema, file-skipping, and initial conditions for fitting on each data set.
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Cross-validation involves fitting the model to only part of the data and testing the model on the part that isn't used for fitting.
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As someone who works on these types of migrations and data centers regularly, you'd be surprised at what can severely delay your server infrastructure getting into place at the desired time.
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You can argue how great Python is for parsing terrible data formats.
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The place I use is happy to bin any that are past best, and when one showed worrying signs a few days after fitting they replaced it, no quibble.
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Like all theories, it's open to new data.
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Low bandwith can throttle data and make the ping higher.
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Theorists try to get their work experimentally tested by experimentalists, and experimentalists give theorists experimental data which theorists use to build theories/models.
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