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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 -*-2 R8 ^% C2 M5 o# D: X1 H
( ?2 t+ F& r: ximport math
6 S$ r5 ^/ @# T/ Y" G# E- G) bimport sys
! P! o( \2 n3 X: [: K+ U3 {from texttable import Texttable5 I) C! C# m% N; `* D9 @4 D- P5 K- H* z% c
4 `# D$ R2 B7 z" j
; _, e8 a' a- _9 Y+ V) Q/ y2 S#; y# ?2 l7 p" b- j' Z* O# z
# 使用 |A&B|/sqrt(|A || B |)计算余弦距离9 D- ~" ?9 @1 Q1 o: C1 K
#, I4 I7 d+ M1 d. f- `3 `+ h: N4 O% x6 ]
#3 e) ~; e* d: d5 z# F8 r
#
3 D- p8 Q: k7 g* i7 ldef calcCosDistSpe(user1,user2):8 q5 o& x& p; ^& O
avg_x=0.0& V; h; D8 A \5 Y8 [! x
avg_y=0.0+ y6 c! k0 x/ y( A
for key in user1:
' [1 C2 U5 {; ^, ], G avg_x+=key[1]" _, J( N9 E+ J0 {8 A; n
avg_x=avg_x/len(user1)
! |* r7 a/ j$ \8 {: b" m # r$ o! x$ U1 P6 u# b0 E8 E
for key in user2:
% F& H" _6 _( C avg_y+=key[1]
T2 [3 q% }4 k& j avg_y=avg_y/len(user2)
" h' O, Z3 o8 Q. p 8 U1 `1 e4 p- F2 f% _( r8 }
u1_u2=0.0
7 S: Y; k- u5 m" C2 ]# A) v# c for key1 in user1:8 r+ m3 ~6 \: L7 {
for key2 in user2:3 |8 f8 m, K2 y# K7 P! `
if key1[1] > avg_x and key2[1]>avg_y and key1[0]==key2[0]:
% k0 k4 J5 E E; t/ d2 q; T& O5 n u1_u2+=1
+ z# ~1 X: h. v! b: h; ~, z; V u1u2=len(user1)*len(user2)*1.00 a+ ~/ e2 L9 L" T& U
sx_sy=u1_u2/math.sqrt(u1u2)
" ]% b) Q6 T$ j6 O! C% ?5 l4 T4 G return sx_sy. W& S( \6 D. }
5 S2 j `' O6 Y4 s# B8 d* P* b6 Q; [* Y4 D/ \( G# I x
#( G7 W; k [, O) } `
# 计算余弦距离
; y, d) ~6 h7 m" Y, U$ D#! E) b* [* C1 `* K: n) X
#
0 m! `; U5 u9 f6 f# Q# L. }def calcCosDist(user1,user2):
8 i. z, j( L4 b1 B& N7 N sum_x=0.0
( s+ ]% _) T3 \# N sum_y=0.0' X) Q2 x' c. g( p9 i- h
sum_xy=0.06 H. O2 c$ j6 i* l
for key1 in user1:
. Y7 A2 w' x7 w( F, r" r6 l% r for key2 in user2:1 a0 x0 u- g/ C* n; i! ~
if key1[0]==key2[0] :
; O9 |* A: `/ e! h0 o7 Z sum_xy+=key1[1]*key2[1] L% e3 a. b M' l! r" `
sum_y+=key2[1]*key2[1]
9 t/ Z2 R- _5 S sum_x+=key1[1]*key1[1]
4 q2 a5 Q. W9 x% X0 Z 6 F4 D$ W6 L8 M! |" t/ H9 x [8 ?
if sum_xy == 0.0 :# d4 y K7 g- G- N+ B
return 0
2 n7 Q C* }/ O) I \" Y! D4 i5 x sx_sy=math.sqrt(sum_x*sum_y) ; s, n, i) X% _! q+ G4 |8 v* [
return sum_xy/sx_sy
; `8 k6 N3 J: r6 Q) h# X
1 G# z |# ^1 P$ I! u& }' @, D5 [4 u, ~2 U
#9 ?* C7 V2 d& q! l2 {+ a" H
#5 Z' l) z$ D6 x1 M$ F5 N
# 相似余弦距离
/ v( D$ O) \$ c#
/ w2 A, O! H* Q: E) w, _! E#( r k; y, \0 A# l
#: l1 `, g0 w1 K% G w! {9 ^& d' c
def calcSimlaryCosDist(user1,user2):8 a w/ ]" k5 o
sum_x=0.0/ s* t) D \% a6 A: [) X; Y9 k
sum_y=0.0/ Q7 x, U9 h) {+ K' `# A
sum_xy=0.0* H% X$ E8 _9 K& o8 q G- \
avg_x=0.0
& F- Y% Y. D% a9 D avg_y=0.0; D/ {- M! z; b
for key in user1:
6 `) I! P: a5 S7 S avg_x+=key[1]
p* y4 X6 i* T* [' B avg_x=avg_x/len(user1)
: C% N4 G$ j; f& H6 y 8 t5 _. F) R2 g
for key in user2:
' y4 {# l- R6 ~) Y ?+ a; W avg_y+=key[1]
$ [/ E0 Y d2 C. L) ] avg_y=avg_y/len(user2)
- N; @$ T) k8 {$ ~
0 v+ B& o$ Z7 [& [8 g for key1 in user1:) r9 s: M @4 b F9 u) [
for key2 in user2:* f: A9 E" Q8 H4 Z2 b# a
if key1[0]==key2[0] :! W v/ t, m$ o8 v' k
sum_xy+=(key1[1]-avg_x)*(key2[1]-avg_y)+ Q- c1 K! Z, ?/ a' k$ r% \
sum_y+=(key2[1]-avg_y)*(key2[1]-avg_y)
; G' T2 ?7 `7 B* V3 |5 } sum_x+=(key1[1]-avg_x)*(key1[1]-avg_x)
$ m4 d7 H0 K' [( y& _7 {
* N* b. L" M7 C0 b if sum_xy == 0.0 :, t9 R& p: w0 l8 j+ p+ p' Y
return 0
. s$ j$ Z+ f( }, J$ s sx_sy=math.sqrt(sum_x*sum_y) 7 t' u9 L4 g5 ^- K+ C
return sum_xy/sx_sy
( q& x4 i, \- w+ i& t * `+ N! o. k+ e T5 L8 z$ a
( S2 s$ y2 b y5 W#
/ s5 ?4 v& l( A0 O4 z) {, ?# 读取文件
) }+ f% E* |" e( l3 i#0 S- `6 f6 u, n% }/ Y) {
#7 \1 L. [! m* u5 \7 Y8 }9 v
def readFile(file_name):
2 S7 B4 \+ K4 B5 y: b0 f$ ] contents_lines=[]$ T" f+ Q% p9 T E$ x
f=open(file_name,"r")
( E" `" `: H/ N& s contents_lines=f.readlines()
; Q9 L4 l0 ]0 ], Y f.close()/ R8 \2 o$ S B- ^
return contents_lines( j& m, {5 T! B1 x" @9 w
' r- n, [/ s% j h
. I5 ]/ ]: [' t6 D% }! [
6 y5 `; K1 ~" O$ z' \+ x
#
) i3 @: @8 ?( H/ v+ P: K# 解压rating信息,格式:用户id\t硬盘id\t用户rating\t时间
" ~8 u. J) U' A/ z. B# 输入:数据集合
J5 ^7 L' P2 s c6 F [0 f p# 输出:已经解压的排名信息+ W/ Z6 e) u/ b& x
#1 s9 v8 G+ \+ ~6 O) r
def getRatingInformation(ratings):. h5 Y$ J9 m3 \4 K9 |$ r5 G+ b
rates=[]
1 C- t: _% |7 L; [. I for line in ratings:
( E9 n% A/ \6 [0 w* }/ ] rate=line.split("\t")/ I+ G* N+ C" O4 |+ i$ t7 ?
rates.append([int(rate[0]),int(rate[1]),int(rate[2])])
6 P4 k, f% R* h* R8 b return rates! ^5 B& B* a+ j9 {
* Z+ _0 M+ Y5 w4 \7 ]6 \( r
2 ]. T0 K1 f8 L1 K: v#* ]. p+ [6 }( B
# 生成用户评分的数据结构 m: P9 C1 R$ w* i) _
# ) E3 |& Y* q- z6 [
# 输入:所以数据 [[2,1,5],[2,4,2]...]
. ]+ ]0 I/ F. m- b) E0 G" e$ W# 输出:1.用户打分字典 2.电影字典
9 g& f [8 t: z4 ^8 D9 k# 使用字典,key是用户id,value是用户对电影的评价,8 s9 L2 H1 E: M. F9 x% q
# 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25 d/ p& c/ L& T
#6 a2 x4 ]; Y* {
def createUserRankDic(rates):
6 R; C, I4 M5 J- z; Q2 i user_rate_dic={}
- |9 v. K* b& k/ j J item_to_user={}% o( {- j9 m5 G8 x/ F1 d& M
for i in rates:
! D0 G/ x( j: Q, o user_rank=(i[1],i[2])
1 V- S* N) v9 u4 I+ i2 O if i[0] in user_rate_dic:' r8 }5 _9 K) ^% E! t, P+ i2 A
user_rate_dic[i[0]].append(user_rank)
8 u) B: r- R' { else:
. n L& w# `4 k+ f' i/ R m user_rate_dic[i[0]]=[user_rank]+ i9 A* O! H! O& ?- n" S w
3 `2 J1 ]0 ?/ B% v6 r" I/ o if i[1] in item_to_user:
4 E" N. G6 n7 y item_to_user[i[1]].append(i[0])" L( H4 g! _" Y. Q. h9 S; h+ l5 {
else:3 \( p1 c; U$ x! w0 Q2 X
item_to_user[i[1]]=[i[0]]
T: ], q# Y; o9 |7 Q . ]! S* ]! h! p/ B: E
return user_rate_dic,item_to_user" d* H; G1 O: @$ S
2 \# K2 T) }3 l' E* N7 K2 [, c+ R
- B6 s% {+ s) b7 e# W6 h, W P; i8 [
# 计算与指定用户最相近的邻居
; w; K/ G. _1 @1 ?6 N$ {# 输入:指定用户ID,所以用户数据,所以物品数据
9 Z( \1 s6 W1 u4 |4 m \5 z# 输出:与指定用户最相邻的邻居列表
4 \% `; C( A- S- u#9 m3 v6 x6 S' w D; H0 i) H6 h( _
def calcNearestNeighbor(userid,users_dic,item_dic):$ ^ |+ G+ j; Y5 k) P7 r3 S& J
neighbors=[]/ X6 V7 O; n1 A# I- y
#neighbors.append(userid)' d; Q5 W) \6 p3 `0 L) K
for item in users_dic[userid]:
8 Q+ ~" y+ U' G) u) q$ o3 q for neighbor in item_dic[item[0]]:1 A& Q. L2 n3 ?% E9 {
if neighbor != userid and neighbor not in neighbors: * Q. a3 n( k0 J9 ~+ E8 z4 {& c
neighbors.append(neighbor)
Q: w: ]1 s; B
' G- F7 J) X- l! y: c neighbors_dist=[]
4 v2 J5 X6 c: V3 w9 p/ t for neighbor in neighbors:) k) r' J4 X r
dist=calcSimlaryCosDist(users_dic[userid],users_dic[neighbor]) #calcSimlaryCosDist calcCosDist calcCosDistSpe
- a0 Q0 u( z: [2 `; \ neighbors_dist.append([dist,neighbor])
. M- o8 [4 m) N/ \ neighbors_dist.sort(reverse=True)' ^/ r q/ b1 U( N; V6 T2 G
#print neighbors_dist! r0 l: U7 U3 V2 | a+ E8 H
return neighbors_dist
' W9 R `1 o3 J: N9 ^" G% }! N7 l, Y! C
8 ?, u& r! \3 | |8 V7 t9 |" }0 l4 l( N5 k v2 v5 y" U/ L
#/ P7 \$ T' \7 F2 Q7 [2 w
# 使用UserFC进行推荐
3 t$ p ?, v+ D7 J/ E0 }9 w% ^( B# 输入:文件名,用户ID,邻居数量/ U3 y5 ~; e5 l* t) I* y; ?3 d
# 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7 l2 s* E/ Z8 `( i3 c
#, E# C# A5 B0 _ i( I
def recommendByUserFC(file_name,userid,k=5):( u% i" `$ ?; k8 |' F4 S5 |
6 U, J8 q+ U2 n* a& }
#读取文件数据- a. N! j; i, |2 [5 A, `, [% \% X: i5 H
test_contents=readFile(file_name)
; N. K2 a" `/ x9 t" ~ ^ ( L3 \# b' O) Z" \8 [4 M
#文件数据格式化成二维数组 List[[用户id,电影id,电影评分]...] , L6 S3 c7 U% l9 n# u' e
test_rates=getRatingInformation(test_contents)1 x. ?" k3 ~$ M9 f8 p, T% e
% P; ]2 S8 M( x+ ^) {5 }& s #格式化成字典数据 1 ]# j4 l4 @1 j3 s& X( m$ B( [
# 1.用户字典:dic[用户id]=[(电影id,电影评分)...] `) D4 I, D3 k/ X5 T. l
# 2.电影字典:dic[电影id]=[用户id1,用户id2...]0 C- y0 w0 h; v* u- o0 k5 B; ?
test_dic,test_item_to_user=createUserRankDic(test_rates)
\# Y1 I& n+ j3 [4 Z! q
" U* R8 K! M. m2 u: e #寻找邻居
, H7 g7 G7 J; C neighbors=calcNearestNeighbor(userid,test_dic,test_item_to_user)[:k]
$ W9 S& i4 a4 A; T
. t( f2 j$ b( r: {& W recommend_dic={}" |% Z5 o1 B7 o& O% a; r
for neighbor in neighbors:
# I, v& A" e" m4 X neighbor_user_id=neighbor[1]& \* V3 V8 d, b/ a* v/ r
movies=test_dic[neighbor_user_id]4 ^% l3 Y& w. a" ?: @' ]' R C) Z8 O
for movie in movies:
; f2 P$ w& S' z$ X #print movie/ F# t6 K1 ~6 V; U2 S2 e( Q
if movie[0] not in recommend_dic:& ]/ E; ^5 L2 e2 k: R* z* m% x0 F9 [
recommend_dic[movie[0]]=neighbor[0]9 h, x7 h0 j8 T, K ? B4 y" i9 L) J! f
else:
$ s0 O/ h; J6 l% Q# R- a" ] recommend_dic[movie[0]]+=neighbor[0]. L1 C) b8 s }6 v* s3 L/ @9 _0 L
#print len(recommend_dic)
& e: Z" M) g& x4 ~6 L
/ V) Y- N P& [ ~) _" p #建立推荐列表; b, {7 I* v M7 B8 `( U
recommend_list=[]
. |+ Z. a+ S1 y4 n8 G for key in recommend_dic:, ]8 ?9 @3 }2 _# s
#print key: X" v3 L' i) l
recommend_list.append([recommend_dic[key],key]), F4 k6 N4 [; @2 T" d. N
5 K8 _" i, i- G* s# `
! D/ [4 h# P/ {4 g* M" V* j/ g3 _" U
recommend_list.sort(reverse=True)
6 ]% a9 ]2 \" o #print recommend_list
+ K- l0 q& v2 {: L! \ user_movies = [ i[0] for i in test_dic[userid]]
- E! i; B9 o5 X& o8 Y# O# \: [0 a) a0 c
return [i[1] for i in recommend_list],user_movies,test_item_to_user,neighbors
+ o" E: P6 y m* G; c* i2 q3 i f$ c: w' I1 d% Q' q% a* ?
4 C5 a4 \1 X2 U8 E+ `
1 Z. [8 H8 q8 \8 R' T#7 w6 V" n6 Q' q \3 S+ q
#; W' ], V7 |- r9 ?# k' W; E
# 获取电影的列表! \/ u) m" @% ~( B+ Y7 {/ j @) C
#$ p$ y6 M0 s3 p* z
#2 c. S0 s: z2 S0 T! Q2 z
#
2 z+ T3 e) S8 V1 j C( ]def getMoviesList(file_name):3 J/ n# }: J0 E/ i& _) c6 l a
#print sys.getdefaultencoding()4 W I' y2 p" U& d/ Q m i
movies_contents=readFile(file_name)
* r2 [7 ?& t: O1 X9 c movies_info={}
+ \7 F$ d( Z$ H ]7 n for movie in movies_contents:
2 K7 U" i4 U9 I, Q# r7 s# a" t3 g1 r movie_info=movie.split("|")
+ z5 r1 ^- o- h/ o( e. o movies_info[int(movie_info[0])]=movie_info[1:]
S& P- Z3 _; p8 b. I. v" ]! { return movies_info4 A8 W: G! O( {3 V- i
' \7 ^; g' ]. k. o7 F# N, ~
" B7 O% f( I0 g( I5 y' v4 Z
4 o% n: j% Q% ]: F" C S9 B#主程序
+ ]% I9 b! \. w7 X( a0 {0 B2 I#输入 : 测试数据集合
# I9 C: d+ O/ `: |" B0 w. \if __name__ == '__main__':
& i$ h% X0 N) h7 T; s; W reload(sys)- z& r n/ y, f6 _
sys.setdefaultencoding('utf-8')
4 N9 M' W! o. G# ?# O movies=getMoviesList("/Users/wuyinghao/Downloads/ml-100k/u.item")9 W' s5 T) a; c! B, k
recommend_list,user_movie,items_movie,neighbors=recommendByUserFC("/Users/wuyinghao/Downloads/ml-100k/u.data",179,80)# p$ I, T& q& Q: {
neighbors_id=[ i[1] for i in neighbors]5 k( W$ k& f$ @; @0 ]/ e1 }4 V. [
table = Texttable()
) K! U* P( ^3 B$ M4 v table.set_deco(Texttable.HEADER)
- n3 Y4 R- N4 W4 z* I4 z/ S table.set_cols_dtype(['t', # text
! m2 M( |& y7 ^6 f2 C* b- M 't', # float (decimal)" S& A; J; d9 L; h& a2 {5 e U
't']) # automatic
3 v1 w% ^8 ~! e& B table.set_cols_align(["l", "l", "l"])" e8 ~" `) j: p( I' n0 r0 G
rows=[]
4 q7 B' {- W' i2 D& b rows.append([u"movie name",u"release", u"from userid"])
0 M& d/ x# N) p% \4 z for movie_id in recommend_list[:20]:/ ]" u) a9 a0 C
from_user=[]
$ w' g2 [, o v for user_id in items_movie[movie_id]:9 S$ I! n9 J; S5 {4 T5 A0 H" k( Y
if user_id in neighbors_id:
" Y' u4 ]- e' u9 J4 f from_user.append(user_id)0 [& s5 `4 X8 F2 s, E
rows.append([movies[movie_id][0],movies[movie_id][1],""])
# M/ g% N* l5 |+ I( ~# G table.add_rows(rows)" p. p# n: s. w: \; x2 L
print table.draw() |
|