Edited, memorised or added to reading queue

on 07-Jun-2024 (Fri)

Do you want BuboFlash to help you learning these things? Click here to log in or create user.

Flashcard 7629863783692

Tags
#DAG #causal #edx
Question
the most important take-home message: we need expert knowledge to determine if we should adjust for a variable. The statistical criteria are [...] to characterize confounding and confounders.
Answer
insufficient

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
the most important take-home message: we need expert knowledge to determine if we should adjust for a variable. The statistical criteria are insufficient to characterize confounding and confounders.

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629866405132

Question

Predictive customer scores

The company develops analytics—often using several types of machine-learning algorithms—to understand and track what is influencing customer satisfaction and business performance, and to detect specific events in customer [...].

Answer
journeys

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
cs—often using several types of machine-learning algorithms—to understand and track what is influencing customer satisfaction and business performance, and to detect specific events in customer <span>journeys. <span>

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629867453708

Question

Predictive customer scores

The company develops analytics—often using several types of machine-learning algorithms—to understand and track what is [...] customer satisfaction and business performance, and to detect specific events in customer journeys.

Answer
influencing

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Predictive customer scores The company develops analytics—often using several types of machine-learning algorithms—to understand and track what is influencing customer satisfaction and business performance, and to detect specific events in customer journeys.

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629868502284

Question

Predictive customer scores

The company develops analytics—often using several types of machine-learning algorithms—to understand and track what is influencing customer satisfaction and business [...], and to detect specific events in customer journeys.

Answer
performance

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Predictive customer scores The company develops analytics—often using several types of machine-learning algorithms—to understand and track what is influencing customer satisfaction and business <span>performance, and to detect specific events in customer journeys. <span>

Original toplevel document (pdf)

cannot see any pdfs






Annotation 7629869813004


 #causality #has-images #statistics
A common type of non-causal association that makes total association not causation is confounding association
statusnot read reprioritisations
last reprioritisation on suggested re-reading day
started reading on finished reading on


Parent (intermediate) annotation

Open it
We refer to the flow of association along directed paths as causal association. A common type of non-causal association that makes total association not causation is confounding association. In the graph in Figure 3.20, we depict the confounding association in red and the causal association in blue

Original toplevel document (pdf)

cannot see any pdfs



Flashcard 7629871910156

Tags
#causality #has-images #statistics


Question
Consider the following general kind of path, where → · · · → denotes a directed path: 𝑇 → · · · → 𝑍 ← · · · ← 𝑌 . [...] on 𝑍 , or any descendant of 𝑍 in a path like this, will induce collider bias
Answer
Conditioning

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Consider the following general kind of path, where → · · · → denotes a directed path: 𝑇 → · · · → 𝑍 ← · · · ← 𝑌 . Conditioning on 𝑍 , or any descendant of 𝑍 in a path like this, will induce collider bias

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629873220876

Tags
#DAG #causal #edx
Question

Two sources of bias:

- common cause ([...])

- conditioning on common effect (selection bias)

Answer
confounding

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Two sources of bias: - common cause (confounding) - conditioning on common effect (selection bias)

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629874269452

Tags
#DAG #causal #edx
Question

Two sources of [...]:

- common cause (confounding)

- conditioning on common effect (selection bias)

Answer
bias

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Two sources of bias: - common cause (confounding) - conditioning on common effect (selection bias)

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629876890892

Question
Why use a survey to ask customers about their experiences when data about customer interactions can be used to predict both [...] and the likelihood that a customer will remain loyal, bolt, or even increase business?
Answer
satisfaction

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Why use a survey to ask customers about their experiences when data about customer interactions can be used to predict both satisfaction and the likelihood that a customer will remain loyal, bolt, or even increase business?

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629879250188

Tags
#causality #has-images #statistics


Question
If we condition on a descendant of 𝑇 that isn’t a mediator, it could [...] a path from 𝑇 to 𝑌 that was blocked by a collider. For example, this is the case with conditioning on 𝑍 in Figure 4.13. This induces non-causal association between 𝑇 and 𝑌 , which biases the estimate of the causal effect
Answer
unblock

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
If we condition on a descendant of 𝑇 that isn’t a mediator, it could unblock a path from 𝑇 to 𝑌 that was blocked by a collider. For example, this is the case with conditioning on 𝑍 in Figure 4.13. This induces non-causal association between 𝑇 and 𝑌 , which biase

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629880560908

Tags
#causality #statistics
Question

𝔼[𝑌 | do(𝑡), 𝑍 = 𝑧] vs 𝔼[𝑌 | 𝑍 = 𝑧]

𝔼[𝑌 | 𝑍 = 𝑧] simply refers to the expected value in the (pre-intervention) population where individuals take whatever treatment they would [...] take ( 𝑇 ). This distinction will become important when we get to counterfactuals...

Answer
normally

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
𝔼[𝑌 | do(𝑡), 𝑍 = 𝑧] vs 𝔼[𝑌 | 𝑍 = 𝑧] 𝔼[𝑌 | 𝑍 = 𝑧] simply refers to the expected value in the (pre-intervention) population where individuals take whatever treatment they would normally take ( 𝑇 ). This distinction will become important when we get to counterfactuals...

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629883182348

Tags
#causality #statistics
Question
If all the paths between two nodes 𝑋 and 𝑌 are [...], then we say that 𝑋 and 𝑌 are d-separated.
Answer
blocked

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
If all the paths between two nodes 𝑋 and 𝑌 are blocked, then we say that 𝑋 and 𝑌 are d-separated.

Original toplevel document (pdf)

cannot see any pdfs






Annotation 7629884755212

#Linux

If you have a list of files, but you only want to delete files older the a certain date, for example, a maildir folder with 5 years worth of email, and you want to delete everything older then 2 years, then run the following command.

find . -type f -mtime +730 -maxdepth 1 -exec rm {} \;
statusnot read reprioritisations
last reprioritisation on suggested re-reading day
started reading on finished reading on

How to delete all files before a certain date in Linux
How to delete all files before a certain date in Linux Posted on: September 15, 2015 If you have a list of files, but you only want to delete files older the a certain date, for example, a maildir folder with 5 years worth of email, and you want to delete everything older then 2 years, then run the following command. find . -type f -mtime +XXX -maxdepth 1 -exec rm {} \; The syntax of this is as follows. find – the command that finds the files . – the dot signifies the current folder. You can change this to something like /home/someuser/mail/somedomain/



Annotation 7629887376652

#deep-learning #keras #lstm #python #sequence

The choice of activation function depending on problem

Regression: Linear activation function, or linear , and the number of neurons matching the number of outputs. This is the default activation function used for neurons in the Dense layer.
statusnot read reprioritisations
last reprioritisation on suggested re-reading day
started reading on finished reading on


Parent (intermediate) annotation

Open it
format that predictions will take. For example, below are some common predictive modeling problem types and the structure and standard activation function that you can use in the output layer: <span>Regression: Linear activation function, or linear , and the number of neurons matching the number of outputs. This is the default activation function used for neurons in the Dense layer. Binary Classification (2 class) : Logistic activation function, or sigmoid , and one neuron the output layer. Multiclass Classification (> 2 class) : Softmax activation function, or

Original toplevel document (pdf)

cannot see any pdfs



Flashcard 7629890522380

Tags
#causality #statistics
Question
A potential outcome 𝑌(𝑡) is distinct from the [...] outcome 𝑌 in that not all potential outcomes are observed
Answer
observed

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
A potential outcome 𝑌(𝑡) is distinct from the observed outcome 𝑌 in that not all potential outcomes are observed

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629891833100

Tags
#Shell #linux
Question
Answer
--expire

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
How to Force User to Change Password at Next Login in Linux User name: ravi # passwd --expire ravi

Original toplevel document

How to Force User to Change Password at Next Login in Linux
User name: ravi # passwd --expire ravi How to Force User to Change Password at Next Login in Linux Using passwd Command To force a user to change his/her password, first of all the password must have expired and to cause a u






Flashcard 7629893668108

Tags
#causality #statistics
Question
[...] assumption is asymmetric; “ 𝑋 is a cause of 𝑌 ” is not the same as saying “ 𝑌 is a cause of 𝑋
Answer
Causal edges

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Causal edges assumption is asymmetric; “ 𝑋 is a cause of 𝑌 ” is not the same as saying “ 𝑌 is a cause of 𝑋

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629895503116

Tags
#causality #statistics
Question
Whenever, do(𝑡) appears after the [...], it means that everything in that expression is in the post-intervention world where the intervention do(𝑡) occurs.
Answer
conditioning bar

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Whenever, do(𝑡) appears after the conditioning bar, it means that everything in that expression is in the post-intervention world where the intervention do(𝑡) occurs.

Original toplevel document (pdf)

cannot see any pdfs






Flashcard 7629896813836

Tags
#causality #statistics
Question
Positivity is the condition that [...] of the data with different covariates have some probability of receiving any value of treatment
Answer
all subgroups

statusnot learnedmeasured difficulty37% [default]last interval [days]               
repetition number in this series0memorised on               scheduled repetition               
scheduled repetition interval               last repetition or drill

Parent (intermediate) annotation

Open it
Positivity is the condition that all subgroups of the data with different covariates have some probability of receiving any value of treatment

Original toplevel document (pdf)

cannot see any pdfs