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Logistic Regression model in R - academy writing research paper based on live data analsys

Project title: Logistic Regression model in R - academy writing research paper based on live data analsys

Project deadline: 3 days.

Project goals:

0. Spend some time to talk with me (the project ownder) and chat with me to get better understanding of model

1. connect to my public server where R-server is installed over public IP

- you get all the info to be able to connect to server

- the data is in MySQL table on the same server

- R can allready read data from Mysql database table (tested)

2. Write R script on R-server that would create Logistic Regression model in R

- connect to Mysql server in Rserver an fetch the data from table (tested myself and it works)

- construct Rscript to create Logistic Regresion model based on data from table

- train the model

- Interpret the results of our logistic regression model in detail using simple layman's terms

- test the model and assess the predictive ability of the model

- create some graphs and interpret them (describe them)

- create a conslusion

3. Deliverables:

- Deliver the Rscript code that generated the result table

- Write a word documnet report with permissa, model descrption, model validation, created graphs and conslusion

4. requered tools: Internet connection and latest Firefox/Chrome browser

5. Quality of work goals: Academic paper level reqiured with detailed explanations of created model backed up with high quality academic type of references (books) available online.

Milestone-1. Connect to server, write Rscript generate a model.

Milestone-2. Describe every line of the R-Script code, backup with references in manual and links to example

Milestone-3. Detailed report with final conslusion about permissa. (Permissa must be confirmed and model should be confirmed valid).

Submission deadline: Sunday, April [login to view URL] 2018. 15:00 CET.

- binomial logistic regression

data domain description:
We have a Mysql database table (one large table with milions of records).
The table structure is:
- date: the date the sample data is collected
- serial_number: the serial number of disk drive unit
- model: the model of the drive
- capacity_bytes - capacity of disk drive in bytes (not relevant)
- failure - a flag if the drive has failed (died) with value 1 if it is, or value if it is not. If the drive has failed (died) then we can train the model with params from this specific unit (serial_number)
The rest of the columns are values that are "predictors" to the "failure" event
- SMART_5_raw,
- SMART_5_normalized,
- SMART_187_raw,
- SMART_187_normalized,
- SMART_188_raw,
- SMART_188_normalized,
- SMART_197_raw,
- SMART_197_normalized,
- SMART_198_raw,
- SMART_198_normalized

Hypothesis to prove:
One can use SMART parameters to predict the failure of disk drive unit!
If the RAW value of the SMART params is greater than zero for the SMART stat listed

validate the hypothesis data:

Operational drives with one or more of our five SMART stats greater than zero – 4.2% (not failed)
Failed drives with one or more of our five SMART stats greater than zero – 76.7% (failed)

That means that 23.3% of failed drives showed no warning from the SMART stats we record. Are these stats useful?
Conlusion to achieve: SMART PARAMS are a sign of impending drive failure 76.7% of the time.



More reading here:
https://www.backblaze.com/blog/what-smart-stats-indicate-hard-drive-failures/


Ικανότητες: MySQL, Γλώσσα Προγραμματισμού R, Research Writing, Στατιστικά

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Σχετικά με τον Εργοδότη:
( 0 αξιολογήσεις ) Trnovec Bartolovečki, Croatia

Ταυτότητα Εργασίας: #16689827

12 freelancers are bidding on average €167 for this job

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aki003iitr

My profile is as follows:- 4 years of experience in data [login to view URL] science and analytics professional with excellent coding skills in R and Python .  - Proficient in R, Python, SQL,Matlab ; Hands on experience Περισσότερα

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schoudhary1553

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prolificwriter92

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HajjiO

Hello, I've done very similar work when I've done multiple regression in R and connect the results of the fitted observations to MySQL using ODBC package. I really can help you in time Relevant Skills and Experience Περισσότερα

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alperenelibol

I have over 3 years of experience with R. Though I generally work with biostatistics data, I enjoy using statistical learning methods in various types of domains. Feel free to check my profile or contact me for further Περισσότερα

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nasrinlipi

Hello there, I think I can help you with this project. I have lots of experience in handling R language, especially logistic regression. In my Bs project, I worked on multilevel logistic regression analysis. It w Περισσότερα

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