Can access to Machine learning repository at U of California?

I am practicing Machine Learning training book.

I wanted to practice the part, "Building classification Models" and there is a download site, archive.ics.uci.edu/ml/datasets/Heart+Disease.

However, I can not find the website. Because there are many attributes for the heartdataAll.mat, I would like to know what they mean.

I was hopting to get data description at the website, but the website is not available.

I hope to get some help here. Thank you for reading.

[Walter Roberson]

The web page is still there, http://archive.ics.uci.edu/ml/datasets/Heart+Disease same place you indicated. The attributes are all described there.

[Image Analyst]

Did you click the Download link?

[Alice Kim]

Thank you so much for your help. This is the site address on the book and I clicked the site yesterday and a minute ago. However, I have still same problem to access the website with the error message: ERR_CONNECTION_TIMED_OUT. It is very strange because you can go but I can not go. Then there is not the website matter, but the problem might be my computer.

[Walter Roberson]

Is it possible that you have VPN or Proxy set up on your computer? That could interfere with reaching the site.

Hypothetically, there could also be a geographic block put up by the site. Which country are you located in?

[Alice Kim]

I am located at Seoul in Korea. Thank you for your comment.

[Walter Roberson]

I would not expect the site to block South Korea.

I suggest you try from a different computer.

[Alice Kim]

Thank you. I did ask to my colleague next to me. Same error occurred. Probably I am checking out the settings. (ㅠㅠ) Thank you.

[Walter Roberson]

Data Set Information:

This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "goal" field refers to the presence of heart disease in the patient. It is integer valued from 0 (no presence) to 4. Experiments with the Cleveland database have concentrated on simply attempting to distinguish presence (values 1,2,3,4) from absence (value 0).

The names and social security numbers of the patients were recently removed from the database, replaced with dummy values.

One file has been "processed", that one containing the Cleveland database. All four unprocessed files also exist in this directory.

To see Test Costs (donated by Peter Turney), please see the folder "Costs"

Attribute Information:

Only 14 attributes used:

1. #3 (age)

2. #4 (sex)

3. #9 (cp)

4. #10 (trestbps)

5. #12 (chol)

6. #16 (fbs)

7. #19 (restecg)

8. #32 (thalach)

9. #38 (exang)

10. #40 (oldpeak)

11. #41 (slope)

12. #44 (ca)

13. #51 (thal)

14. #58 (num) (the predicted attribute)

Complete attribute documentation:

1 id: patient identification number

2 ccf: social security number (I replaced this with a dummy value of 0)

3 age: age in years

4 sex: sex (1 = male; 0 = female)

5 painloc: chest pain location (1 = substernal; 0 = otherwise)

6 painexer (1 = provoked by exertion; 0 = otherwise)

7 relrest (1 = relieved after rest; 0 = otherwise)

8 pncaden (sum of 5, 6, and 7)

9 cp: chest pain type

-- Value 1: typical angina

-- Value 2: atypical angina

-- Value 3: non-anginal pain

-- Value 4: asymptomatic

10 trestbps: resting blood pressure (in mm Hg on admission to the hospital)

11 htn

12 chol: serum cholestoral in mg/dl

13 smoke: I believe this is 1 = yes; 0 = no (is or is not a smoker)

14 cigs (cigarettes per day)

15 years (number of years as a smoker)

16 fbs: (fasting blood sugar > 120 mg/dl) (1 = true; 0 = false)

17 dm (1 = history of diabetes; 0 = no such history)

18 famhist: family history of coronary artery disease (1 = yes; 0 = no)

19 restecg: resting electrocardiographic results

-- Value 0: normal

-- Value 1: having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV)

-- Value 2: showing probable or definite left ventricular hypertrophy by Estes' criteria

20 ekgmo (month of exercise ECG reading)

21 ekgday(day of exercise ECG reading)

22 ekgyr (year of exercise ECG reading)

23 dig (digitalis used furing exercise ECG: 1 = yes; 0 = no)

24 prop (Beta blocker used during exercise ECG: 1 = yes; 0 = no)

25 nitr (nitrates used during exercise ECG: 1 = yes; 0 = no)

26 pro (calcium channel blocker used during exercise ECG: 1 = yes; 0 = no)

27 diuretic (diuretic used used during exercise ECG: 1 = yes; 0 = no)

28 proto: exercise protocol

1 = Bruce

2 = Kottus

3 = McHenry

4 = fast Balke

5 = Balke

6 = Noughton

7 = bike 150 kpa min/min (Not sure if "kpa min/min" is what was written!)

8 = bike 125 kpa min/min

9 = bike 100 kpa min/min

10 = bike 75 kpa min/min

11 = bike 50 kpa min/min

12 = arm ergometer

29 thaldur: duration of exercise test in minutes

30 thaltime: time when ST measure depression was noted

31 met: mets achieved

32 thalach: maximum heart rate achieved

33 thalrest: resting heart rate

34 tpeakbps: peak exercise blood pressure (first of 2 parts)

35 tpeakbpd: peak exercise blood pressure (second of 2 parts)

36 dummy

37 trestbpd: resting blood pressure

38 exang: exercise induced angina (1 = yes; 0 = no)

39 xhypo: (1 = yes; 0 = no)

40 oldpeak = ST depression induced by exercise relative to rest

41 slope: the slope of the peak exercise ST segment

-- Value 1: upsloping

-- Value 2: flat

-- Value 3: downsloping

42 rldv5: height at rest

43 rldv5e: height at peak exercise

44 ca: number of major vessels (0-3) colored by flourosopy

45 restckm: irrelevant

46 exerckm: irrelevant

47 restef: rest raidonuclid (sp?) ejection fraction

48 restwm: rest wall (sp?) motion abnormality

0 = none

1 = mild or moderate

2 = moderate or severe

3 = akinesis or dyskmem (sp?)

49 exeref: exercise radinalid (sp?) ejection fraction

50 exerwm: exercise wall (sp?) motion

51 thal: 3 = normal; 6 = fixed defect; 7 = reversable defect

52 thalsev: not used

53 thalpul: not used

54 earlobe: not used

55 cmo: month of cardiac cath (sp?) (perhaps "call")

56 cday: day of cardiac cath (sp?)

57 cyr: year of cardiac cath (sp?)

58 num: diagnosis of heart disease (angiographic disease status)

-- Value 0: < 50% diameter narrowing

-- Value 1: > 50% diameter narrowing

(in any major vessel: attributes 59 through 68 are vessels)

59 lmt

60 ladprox

61 laddist

62 diag

63 cxmain

64 ramus

65 om1

66 om2

67 rcaprox

68 rcadist

69 lvx1: not used

70 lvx2: not used

71 lvx3: not used

72 lvx4: not used

73 lvf: not used

74 cathef: not used

75 junk: not used

76 name: last name of patient (I replaced this with the dummy string "name")

[Alice Kim]

Thank you so much. (oo)(_ _) It is really great help.

Answer 1

[Image Analyst]

This is not a MATLAB question.

Contact the administrators of the University of California web site for how to obtain their data.

[Alice Kim]

I am sorry for this question. I thought that Matlab user might give me help for this situation since I read Machine learning tutorial issued by Matlab course. I will come back after I find the way.

[Star Strider]

No worries, and please do not be sorry for asking your question here.

It is simply that most of us here are not ‘MathWorkers’ (people employed by MathWorks).

Also, we do not have any control over whatever the University of California does.

Please contact the authors of your Machine Learning training book, and ask them for an updated link.