How many times you have heard that your residuals should be independent, normally distributed with mean zero, and with constant variance?

No matter if your answer is zero or a million times. This thread can help you

It doesn't even matter that you don't know about residuals👇

First of all: What is a residual?

It is a synonym for error. It is the difference between the expected output and the output of our model:

Y - Ym

Where Ym is the output of our model. So residuals can be positive or negative and we need them to stay close to zero
1: Independence

We don't want the error in for some input to be dependent on the error for another input

That would mean there is information about the relationship between inputs and outputs that our model is missing and that is present in the residuals2
2: Mean equals zero

Well, this is an intuitive one, isn't it?

We have said already that we need residuals close to zero. There should be both negative and positive residuals.

But we don't want a single huge positive error and then a lot of small negative ones

Let's continue
3: Normally distributed

The mean of the residuals is zero, but that's not enough

We need about 50% of the errors to be negative and the other half to be positive

Also, we need most of the errors to be close to zero

In other words, we need the errors to be normally distributed
4: Constant variance

Last but not least. We need the errors to show a constant variance. This is a property called homoscedasticity 🥵

That means our model is equally good (or bad) for all inputs

Non-constant variance denotes our model is missing relevant information
Generally, if the residuals of your model don't meet all the above requirements we should dump it

But it might depend on the problem

Note that and include a residual analysis in your machine learning pipeline starting right now!!!
And that's it!

I hope you have enjoyed this thread and you have learned something new

I have been kind of inactive these days but I publish content like this one from time to time

So, if you like ML, AI, algorithms, and Comp-Sci in general, consider following

Stay tuned!

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1. Number Verification API

A RESTful JSON API for national and international phone number validation.

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2. OpenAI API

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Trump is gonna let the Mueller investigation end all on it's own. It's obvious. All the hysteria of the past 2 weeks about his supposed impending firing of Mueller was a distraction. He was never going to fire Mueller and he's not going to


Mueller's officially end his investigation all on his own and he's gonna say he found no evidence of Trump campaign/Russian collusion during the 2016 election.

Democrats & DNC Media are going to LITERALLY have nothing coherent to say in response to that.

Mueller's team was 100% partisan.

That's why it's brilliant. NOBODY will be able to claim this team of partisan Democrats didn't go the EXTRA 20 MILES looking for ANY evidence they could find of Trump campaign/Russian collusion during the 2016 election

They looked high.

They looked low.

They looked underneath every rock, behind every tree, into every bush.

And they found...NOTHING.

Those saying Mueller will file obstruction charges against Trump: laughable.

What documents did Trump tell the Mueller team it couldn't have? What witnesses were withheld and never interviewed?

THERE WEREN'T ANY.

Mueller got full 100% cooperation as the record will show.
1

From today, we will memorize the names of 27 Nakshatras in Vedic Jyotish to never forget in life.

I will write 4 names. Repeat them in SAME sequence twice in morning, noon, evening. Each day, revise new names + recall all previously learnt names.

Pls RT if you are in.

2

Today's Nakshatras are:-

1. Ashwini - अश्विनी

2. Bharani - भरणी

3. Krittika - कृत्तिका

4. Rohini - रोहिणी

Ashwini - अश्विनी is the FIRST Nakshatra.

Repeat these names TWICE now, tomorrow morning, noon and evening. Like this tweet if you have revised 8 times as told.

3

Today's Nakshatras are:-

5. Mrigashira - मृगशिरा

6. Ardra - आर्द्रा

7. Punarvasu - पुनर्वसु

8. Pushya - पुष्य

First recall previously learnt Nakshatras twice. Then recite these TWICE now, tomorrow morning, noon & evening in SAME order. Like this tweet only after doing so.

4

Today's Nakshatras are:-

9. Ashlesha - अश्लेषा

10. Magha - मघा

11. Purvaphalguni - पूर्वाफाल्गुनी

12. Uttaraphalguni - उत्तराफाल्गुनी

Purva means that comes before (P se Purva, P se pehele), and Uttara comes later.

Read next tweet too.

5

Purva, Uttara prefixes come in other Nakshatras too. Purva= pehele wala. Remember.

First recall previously learnt 8 Nakshatras twice. Then recite those in Tweet #4 TWICE now, tomorrow morning, noon & evening in SAME order. Like this tweet if you have read Tweets #4 & 5, both.