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TA的每日心情 | 开心 2017-2-7 15:12 |
---|
签到天数: 691 天 [LV.9]以坛为家II
群组: 2013年国赛赛前培训 群组: 2014年地区赛数学建模 群组: 数学中国第二期SAS培训 群组: 物联网工程师考试 群组: 2013年美赛优秀论文解 |
# -*- coding=utf-8 -*- P$ [6 I! l3 [# n
1 H6 a+ o% G4 Q8 l2 pimport math
& F3 Y* q- n+ timport sys
+ M$ _% J) \/ D& }' t$ Rfrom texttable import Texttable
) {% c6 z/ Q9 q9 I& b' y% ]$ Z$ V
. v$ S! _) t+ K
9 H+ J8 h- R1 y" {#
4 U8 t& I+ {& \4 H# 使用 |A&B|/sqrt(|A || B |)计算余弦距离- U1 W1 G& j9 B+ R" G
#
6 @' M; f2 b3 ], i#+ k( [8 p& C: F4 E, C0 v2 n) i
#5 I7 v* R0 i6 m9 A9 d
def calcCosDistSpe(user1,user2):
" S6 K/ y+ t6 S& B avg_x=0.0
5 k: M( g# I2 W6 r avg_y=0.0
4 f! U2 \) e8 N for key in user1:
- z5 V3 ~5 ?, { avg_x+=key[1]
; ~2 X7 V) T, \/ K, ] avg_x=avg_x/len(user1)
6 G9 v* j5 \) v: H" c + i9 m2 O, m+ s; \3 v) `) Z
for key in user2:
+ d9 ~: _( Z% [7 z avg_y+=key[1]
4 E2 L6 I- [9 n, G$ A avg_y=avg_y/len(user2)& n1 G' S9 W/ P
2 R1 r6 D2 Q2 I! j6 x$ O* b5 e
u1_u2=0.0
( T: }/ ?" f5 L( Y- M4 F6 N C for key1 in user1:
' b" _6 k& u. c7 H" g% C for key2 in user2:2 f; f" g5 V! R3 @* D* G
if key1[1] > avg_x and key2[1]>avg_y and key1[0]==key2[0]:: [2 Y8 B4 z$ {( N! B5 `4 `. e
u1_u2+=1: [ k& J* i8 z9 F2 L0 H$ e
u1u2=len(user1)*len(user2)*1.0% U, {- r! G0 ^% r3 m
sx_sy=u1_u2/math.sqrt(u1u2)
w1 x; `# u+ p9 Q return sx_sy* v# d9 S% ^$ m2 C4 d( b7 K
5 \, Q ~; P3 L( X
5 H7 x4 o4 N. z3 K/ ?/ \; v#
% b2 q4 Z0 s( a$ l5 C; y9 N+ d, M# 计算余弦距离
- ~' i' k, D Q8 A#5 O8 @ c9 G h$ `1 g
#
8 U2 W+ c! s. }: j# L' _% [def calcCosDist(user1,user2):
- E6 c. A: c8 w9 ~, f sum_x=0.0- M |3 h' j! x9 {. X( H R
sum_y=0.02 [& I, l9 i( A8 f
sum_xy=0.01 |5 ?# G+ x9 @9 K5 T; o
for key1 in user1:6 g2 Q/ Y0 U2 @/ Q% j2 b5 O
for key2 in user2:' w; l* f% [8 x5 Q/ @4 t
if key1[0]==key2[0] :
9 B- n) A3 Q* u3 U% @5 s- B; x+ B3 ` sum_xy+=key1[1]*key2[1]( ?* ]. Q' K7 v [
sum_y+=key2[1]*key2[1]
0 b, |) U2 U0 C5 a T# ~& e; G sum_x+=key1[1]*key1[1]5 E+ {& w2 W0 x/ B! e* F
9 Y& n. Z1 c5 l1 }7 k: z if sum_xy == 0.0 :
/ p' H% I: S1 l0 N% b8 v return 0# v' a( C* @7 @# L \- {! m `6 |
sx_sy=math.sqrt(sum_x*sum_y) 0 p$ X f8 A5 L( K! ]* T3 C% g
return sum_xy/sx_sy
4 d# X7 }. j5 V/ g) ^& O
3 Z# I# d5 u' k
4 \5 ]4 {! [9 a- g3 G1 b#$ B5 S, i3 i/ R8 ]
#
( p0 H( A/ b r) Z7 M# 相似余弦距离
9 h4 i* z* C0 Z' B; K#/ }: x5 K% }% @7 F r! f* I. b5 n9 v
#
" a9 Y: c- r0 y% z" c1 K( v1 t#; ~5 X+ P, g* G/ a3 C; t
def calcSimlaryCosDist(user1,user2):
4 z8 j8 w3 k" `4 f6 j3 F) ~ sum_x=0.0
1 y+ x& j" m: e$ a9 E sum_y=0.0
: M2 U2 p6 h* T* p4 S6 } sum_xy=0.0! T) C; v4 e% w" P( I
avg_x=0.0. T3 f; M* ]) r ^ l/ t5 l
avg_y=0.09 S- C' |) H* C6 {% C b
for key in user1:
0 W# G6 K$ d; k* `7 A9 o7 Q avg_x+=key[1]' e% `; o, J5 ]' n+ ]6 A
avg_x=avg_x/len(user1)
2 T, i" D0 P! C: Q
2 Z$ R5 n3 p! C+ i6 U for key in user2:
4 P5 m! z) K+ e- D' d+ Q T avg_y+=key[1]
" {1 d8 H7 W H5 P$ Y, K avg_y=avg_y/len(user2)8 u( S1 ?/ F- u% x" \5 d9 W/ k3 S
+ r) d; ~2 ]; S7 h5 H
for key1 in user1:- M" u0 L9 n' R# q5 ~
for key2 in user2:
7 m" n3 z; ?1 \4 ]+ M) U! } if key1[0]==key2[0] :: E% G8 {# S$ Q$ c
sum_xy+=(key1[1]-avg_x)*(key2[1]-avg_y)5 R1 `% \+ z% e1 F$ y
sum_y+=(key2[1]-avg_y)*(key2[1]-avg_y)
1 f4 }; i# Z0 N }/ D9 e sum_x+=(key1[1]-avg_x)*(key1[1]-avg_x)0 A) K* V3 k& ^ c( L
8 B |) Q1 E- X& q0 B3 s if sum_xy == 0.0 :
; d- F' s& {+ d, ` b return 07 Q8 L& n) g$ H& | G9 M6 @& a& L
sx_sy=math.sqrt(sum_x*sum_y) % o; w! c/ H: @! t4 a" }( S7 `
return sum_xy/sx_sy
' n/ Z! t( M: M
0 c- c$ W6 o! p6 m* i
, }4 Y C3 T: V2 Y#
& e- d* f6 A1 u4 l% x# ?! D# 读取文件
" L3 A1 a6 u$ \: ^#
% Z+ {/ k+ J- ^# ~9 M9 Q' ~; T% }#
7 R+ v S) Y( G0 K1 K4 x4 Kdef readFile(file_name):
( ?, [/ f) l$ o8 k0 y$ [ contents_lines=[]
3 R# P' A4 m; t/ \4 x( b) y8 S f=open(file_name,"r")8 S h( x3 o$ `; p4 @! c/ o9 t
contents_lines=f.readlines()# t( R, k1 r4 H5 v5 ^
f.close()
! k1 ~# e8 H( n& `1 K return contents_lines' e: I1 t7 g7 ?0 T, z! v1 U) |
9 o5 G6 j2 Z* V4 c9 d$ _" d o
* k2 _" N/ ^& `5 q( m- c
2 L3 ^# S; P w7 ?& D, F: h#1 D0 J* Q) F. j/ u6 Q2 H' {
# 解压rating信息,格式:用户id\t硬盘id\t用户rating\t时间. ?5 X" k$ m% S( N1 D. f
# 输入:数据集合 y3 F( c: X6 }" S; X |
# 输出:已经解压的排名信息
1 n* t& }5 S4 x- [! @#
; N/ P9 V: O+ }$ s" |def getRatingInformation(ratings):
' J1 T9 U- F: A* c5 T7 F rates=[]- a) O" Z1 A) i* \, Z2 r
for line in ratings:
* t& Q. O* N. u( W3 W* s rate=line.split("\t")
) L3 j! Z# R7 C rates.append([int(rate[0]),int(rate[1]),int(rate[2])])
& m% a$ U8 |8 K: |, O' k return rates4 C, P' Z7 `7 R+ P
9 n! R. [0 `* d2 H" F
: X0 f% d* }/ | O/ P#
1 Z4 w! i8 r$ L8 b: s# T# 生成用户评分的数据结构
[& o" d) g( E# # A9 F: j( m7 }6 Q7 q; `8 E0 ~
# 输入:所以数据 [[2,1,5],[2,4,2]...]
& B3 f& v2 a% ~# 输出:1.用户打分字典 2.电影字典: m2 K4 T0 n. ]
# 使用字典,key是用户id,value是用户对电影的评价,
% y1 y9 n9 J8 p) ?8 w" F) \( C# rate_dic[2]=[(1,5),(4,2)].... 表示用户2对电影1的评分是5,对电影4的评分是2
/ S% O/ P( B7 O' Q/ \: [# S6 e#4 \8 ?5 O0 ^& r# @* h( Q
def createUserRankDic(rates):: \5 B$ X/ h# t9 H
user_rate_dic={}
- S( }5 H7 U. {* v% `6 B item_to_user={}+ t6 l! U) M1 I2 Y5 G Y9 ]
for i in rates:$ v. X3 g: y Z: Y+ u' G$ ]
user_rank=(i[1],i[2])8 @: u4 k2 w" Y6 D5 e, k
if i[0] in user_rate_dic:7 t0 Y, v" t& i v8 ?
user_rate_dic[i[0]].append(user_rank)
% B, x7 n r9 F/ {, a8 N else:
% ]3 g% O7 d. `( y. G. c user_rate_dic[i[0]]=[user_rank], }, ] [& k3 l7 Y [4 p' {3 A
4 P3 M+ t8 q0 D
if i[1] in item_to_user:
) i0 B- k9 L* W% ~4 m item_to_user[i[1]].append(i[0])# e0 a1 f( c V! C
else:4 q3 e3 }% w E8 w5 u* y( S) I
item_to_user[i[1]]=[i[0]]5 k+ Z D) E% T3 k9 w0 m
T4 ]; `( [* V. a3 R return user_rate_dic,item_to_user
" c) F- K) l7 |4 U* S: r0 J* Y- V2 h
( U1 T& }( {8 ~' _, X3 s- a2 t
; s5 F3 ^2 m; ?$ f, I" t# V#
7 s& I7 G4 U( _7 |# 计算与指定用户最相近的邻居
( s' U/ W% @: A% c# 输入:指定用户ID,所以用户数据,所以物品数据
/ G' a4 s9 ~1 k# 输出:与指定用户最相邻的邻居列表; F1 J; Z- m& y! |
#" W4 B' D1 W! M; y, N5 ~$ P
def calcNearestNeighbor(userid,users_dic,item_dic):
4 M0 z6 S% |+ w. s5 ~ neighbors=[]. N3 K1 n5 k6 G0 N
#neighbors.append(userid)
5 v1 E( ?' y) t! L for item in users_dic[userid]:* ~; |, O, ]4 {3 P# \7 d
for neighbor in item_dic[item[0]]:
H8 i- X: R3 X6 u if neighbor != userid and neighbor not in neighbors:
+ y/ Z( @9 b( ~: L2 |# } neighbors.append(neighbor)! Y2 G1 g& K; k
3 J5 K& `: a9 N
neighbors_dist=[]
% G, r" c$ |* R" ]# @ for neighbor in neighbors:# ^, H" w1 p3 h6 _/ J$ l+ I i4 k
dist=calcSimlaryCosDist(users_dic[userid],users_dic[neighbor]) #calcSimlaryCosDist calcCosDist calcCosDistSpe- m& T5 z4 C" u# H+ w0 R
neighbors_dist.append([dist,neighbor]): K' G# x0 d3 { `8 M5 c7 j
neighbors_dist.sort(reverse=True)
; F- u' B) J8 R8 {& ` #print neighbors_dist3 K1 A* [$ d5 X* v4 Z; B
return neighbors_dist! \1 c0 _' j4 A1 i3 }, g) V4 T
' g! _0 Z, l5 K$ f% p
" _& s4 H" R" X
#) C, U3 k3 ^4 X: I) l8 t
# 使用UserFC进行推荐& w6 _8 J+ I; o ]
# 输入:文件名,用户ID,邻居数量/ G% Z! z3 }4 g- s) d. p
# 输出:推荐的电影ID,输入用户的电影列表,电影对应用户的反序表,邻居列表
. |0 X! o/ j I' }8 b, Q#& }7 V2 X$ q2 Z/ z$ j3 C
def recommendByUserFC(file_name,userid,k=5):
, g. Q) `( A1 D K p) `% ]1 g. p* ^
#读取文件数据
1 g5 r8 e J D0 G$ w: v1 M& j& t test_contents=readFile(file_name)
6 ]* Z! d8 O3 f1 K: W
( k0 k+ g) x6 X% b #文件数据格式化成二维数组 List[[用户id,电影id,电影评分]...]
: q" Y5 e! T' |+ {: F test_rates=getRatingInformation(test_contents)
/ a; V8 l; b& }; V( w9 J, w6 f; |4 E
' {/ j( u9 Z/ [& y7 T #格式化成字典数据 2 M u: Y6 ~4 {. w1 v1 q
# 1.用户字典:dic[用户id]=[(电影id,电影评分)...]
4 k/ Q2 f# p2 |" x6 Y. ]6 R # 2.电影字典:dic[电影id]=[用户id1,用户id2...]! l ` V( _4 u# @% q' ~) Y5 S& c
test_dic,test_item_to_user=createUserRankDic(test_rates)
C5 k' c$ \" B# U
: {8 A% u1 W) b1 ] #寻找邻居
* ?3 U2 E; D8 z2 s ]9 J }0 } neighbors=calcNearestNeighbor(userid,test_dic,test_item_to_user)[:k]
8 F! t+ r5 S3 v" W
p& H2 f5 F4 d- y recommend_dic={}4 F, h6 i* s3 @* u" G9 s, p* y
for neighbor in neighbors:7 s9 \9 H" j8 {/ M: N9 T
neighbor_user_id=neighbor[1]; V% V& D4 E' A8 O x% Y/ P
movies=test_dic[neighbor_user_id]+ G( K, D1 r5 [. v# O6 u P7 q6 o
for movie in movies:
4 v% |% K8 @: f0 E* E+ L8 e8 b #print movie( p% a3 E" n/ q6 |
if movie[0] not in recommend_dic:: R' Y9 j: M3 o, D- t
recommend_dic[movie[0]]=neighbor[0]
8 y' K; u4 Q& t: [8 b7 U else:5 g, P% Q8 ?+ E/ Z/ |9 N n( t
recommend_dic[movie[0]]+=neighbor[0]
0 _7 q3 h9 W# U% J& m- ` j #print len(recommend_dic)( Y: P% }8 q6 \; {( M1 F+ `
. u l r9 g$ p
#建立推荐列表
0 P c! N) |! p+ u' e8 a& J" T recommend_list=[]9 @ ~4 P4 H6 ^3 G* E$ g6 \* s
for key in recommend_dic:$ _8 U2 Q( V A5 l5 h5 b9 }
#print key
! i: T4 N: T+ F& }! E recommend_list.append([recommend_dic[key],key])
6 ], c# K, d$ T " R. n5 r) g* O5 z4 U) }
. @6 n" v( m$ U% `8 s& v
recommend_list.sort(reverse=True)2 G/ \5 r. Q. _5 B1 T1 b0 h- e
#print recommend_list+ V5 Z% E2 b8 S
user_movies = [ i[0] for i in test_dic[userid]]
, h( v- ^% Z% P0 \8 t" V' u5 n5 k+ D4 y; f
return [i[1] for i in recommend_list],user_movies,test_item_to_user,neighbors
% n3 f% a9 I. T
" \9 P- l/ S# E$ T6 L4 Z$ \8 v+ s
$ e4 W" ^1 t3 j S) S# b% v2 |7 ]: M$ _% X
#
* L! `8 l: C- f7 ~- S7 [#7 n- V$ z3 V2 J$ [8 O/ B
# 获取电影的列表
2 p6 G& K) Z2 N' f#* }8 ^$ d: G8 ]. Y0 w
#
! e. J" q8 ?: l7 @% W#8 [! Z4 e. I- R3 N) `
def getMoviesList(file_name):
8 S/ `1 H d, s6 A, L& S #print sys.getdefaultencoding()
7 p% b a4 C+ R movies_contents=readFile(file_name)
8 f Y- N& a5 J& l movies_info={}% }- M* C+ I) `0 B6 |0 h2 p- a
for movie in movies_contents:
* F& A0 w% V) o, G5 x movie_info=movie.split("|")
$ h4 i+ J8 F' \7 w# ^ movies_info[int(movie_info[0])]=movie_info[1:]
; e. P4 } W! L2 f, s return movies_info8 w' t/ M/ N5 A1 P/ ]% B
4 _/ j" j5 D \9 l$ P' {- P7 w $ H( ?( q' s0 _# e
5 k2 D/ e8 W# }) F9 [: X# i
#主程序
( q+ t' Q3 v, O R9 Z#输入 : 测试数据集合+ m3 A: A6 G# Z- Z- q. K
if __name__ == '__main__':' }$ `0 n: X J0 ^) _5 I
reload(sys)6 d9 ?% A' a* P
sys.setdefaultencoding('utf-8')) I6 V, ?; V( Z2 D9 F% i7 j9 f4 U
movies=getMoviesList("/Users/wuyinghao/Downloads/ml-100k/u.item")
! s4 I/ I. [% R8 P8 i, H; ` recommend_list,user_movie,items_movie,neighbors=recommendByUserFC("/Users/wuyinghao/Downloads/ml-100k/u.data",179,80)1 h/ a: V' q, d
neighbors_id=[ i[1] for i in neighbors]
- v9 ~8 t& e4 i4 _/ a table = Texttable()" P" u1 s( r' r' E& x% C1 J
table.set_deco(Texttable.HEADER)2 _1 a4 U4 a9 q& S8 y; e. o& q
table.set_cols_dtype(['t', # text ) n1 u+ `: }. }8 A
't', # float (decimal)4 \ ~/ T# L/ l1 b4 [, J4 [ h
't']) # automatic
& q# ~( \7 n( I6 u7 ^2 U. m table.set_cols_align(["l", "l", "l"])- e# ^% F! }' L! E" |
rows=[]' f( A$ w, I* v9 } n' g+ o
rows.append([u"movie name",u"release", u"from userid"])3 k6 {6 k* }/ b$ e
for movie_id in recommend_list[:20]:
6 P _' a l2 a# D- R from_user=[]) o* M( P; I8 B0 [6 n9 R
for user_id in items_movie[movie_id]:
1 |# e2 L+ g2 v6 Z- _9 `, P if user_id in neighbors_id:% L% Y2 n3 ]9 T4 D; a* N
from_user.append(user_id)
) a. f7 M7 _7 }6 K+ b3 N' N! S rows.append([movies[movie_id][0],movies[movie_id][1],""])
/ H9 y/ [1 U' G' [6 S table.add_rows(rows)9 _& k' U, m a3 q* V: p
print table.draw() |
|