This article is about the album by Art Blakey. For the album by Sam & Dave, see Hold On, I'm Comin'.
Hold On, I'm Coming
Studio album by
Art Blakey
Released
1966
Recorded
May 12, 1965 and May 27, 1966 New York City
Genre
Jazz
Length
34:29
Label
Limelight LM 82038
Producer
Jack Tracy and Luchi DeJesus
Art Blakey chronology
Buttercorn Lady (1966)
Hold On, I'm Coming (1966)
Jazz Messengers '70 (1970)
Hold On, I'm Coming is an album by drummer Art Blakey recorded in 1966 (with one track left over from the Gary Bartz debut recording session in 1965 for the album Soul Finger) and originally released on the Limelight label.[1][2]
Contents
1Reception
2Track listing
3Personnel
4References
Reception[edit]
Professional ratings
Review scores
Source
Rating
Allmusic
[3]
Allmusic awarded the album 3½ stars, stating: "Ultimately, this is a very enjoyable if not mindblowing soul-jazz date that offers a very relaxed and subtle view of Blakey."[3]
Track listing[edit]
"Daydream" (John Sebastian) - 3:06
"Hold On! I'm Comin'" (Isaac Hayes, David Porter) - 2:34
"Secret Agent Man" (Steve Barri, P.F. Sloan) - 2:57
"I Can't Grow Peaches on a Cherry Tree" (Camille Monte, Estelle Levitt) - 2:14
"Walking My Cat Named Dog" (Norma Tanega) - 1:51
"Sakeena" (Art Blakey) - 3:43
"Got My Mojo Working" (McKinley Morganfield) - 3:20
"Mame" (Jerry Herman) - 2:59
"She Blew a Good Thing" (Henry Murray Jr., Ronnie Lewis) - 2:18
"Monday, Monday" (John Phillips) - 2:20
"Slowly But Surely" (John Hicks) - 7:07
Personnel[edit]
Art Blakey - drums
Chuck Mangione (tracks 1-10) Freddie Hubbard (track 11), Lee Morgan (track 11) - trumpet
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up vote 2 down vote favorite There is a clear pattern that show for two separate subsets (set of columns); If one value is missing in a column, values of other columns in the same subset are missing for any row. Here is a visualization of missing data My tries up until now, I used ycimpute library to learn from other values, and applied Iterforest. I noted, score of Logistic regression is so weak (0.6) and thought Iterforest might not learn enough or anyway, except from outer subset which might not be enough? for example the subset with 11 columns might learn from the other columns but not from within it's members, and the same goes for the subset with four columns. This bar plot show better quantity of missings So of course, dealing with missings is better than dropping rows because It would affect my prediction which does contain the same missings quantity relatively. Any better way to deal with these ? [EDIT] The nullity pattern is confirmed: machine-learning cor...